ARTHUR D. LITTLE

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ISS U E 0 43

HUMAN
AFTER ALL
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P R I S M : HUMAN AFTER ALL

THE PRISM BOARD

2

Shinichi Akayama

akayama.shinichi@adlittle.com

Etienne Brumauld des Houlieres

brumaulddeshoulieres.etienne@adlittle.com

Rick Eagar

eagar.richard@adlittle.com

Dr. Raymond Khoury

khoury.raymond@adlittle.com

Dr. Michaël Kolk

kolk.michael@adlittle.com

Florence Carlot

carlot.florence@adlittle.com

Michael Majster

majster.michael@adlittle.com

Francesco Marsella

marsella.francesco@adlittle.com

Albert Meige

meige.albert@adlittle.com

Daniel Monzon

monzon.daniel@adlittle.com

Andreas Schlosser

schlosser.andreas@adlittle.com

Ben van der Schaaf

vanderschaaf.ben@adlittle.com

ARTHUR D. LITTLE

Arthur D. Little has been at the forefront of innovation since 1886.
We help companies continuously anticipate, innovate, and transformto achieve sustained business success in today’s disruptive
business environment:– Anticipate future trends and build resilient strategies thatembrace complexity.
– Innovate to deliver more, faster, cheaper products, services,and business models, accessing the best external talent.
– Transform organizations, processes, and cultures tocontinuously adapt.
We are problem solvers and combine deep industry insight, functional
skills, and entrepreneurial flair to find and deliver new solutions. With
our open consulting approach we bring the best global experts to every
assignment, complementing our internal strengths. We are proud to bepresent in the most important business centers around the world, serving
the world’s leading corporations and public sector organizations.

PRISM is published biannually by Arthur D. Little, the global management consultancy. We are eager tohear from our readers! Please address your comments to our editorial office at Arthur D. Little, New Fetter
Place West, 2nd floor, 55 Fetter Lane, London EC4A 1AA, United Kingdom — Telephone: +44 7710 536 471.
Copyright 2024, Arthur D. Little. All rights reserved. Editing and design by Catalyst Comms, London:
info@catalystcomms.co.uk.

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P R I S M : CONTENTSCONTENTSHUMAN AFTER ALL
OP TIMISTIC GLOBAL CEOS FOCUS ON PEOPLE
AND SKILLS IN AN AI FUTURE

8
At a time of unprecedented turbulence, how are global CEOs reacting,
and what strategies are they adopting to move their businesses forward?
Based on the ADL 2024 CEO Insights Study, our lead article finds thatleaders of the world’s largest companies are confident of future success,relying on a combination of people and AI to deliver growth.
Francesco Marsella, Ralf Baron, Petter Killefors, Maximilian Scherr,
Satya Easwaran

THE PEOPLE-CENTRIC L AB OF THE FUTURE— A I - S U P P O R T E D I N N O VAT I O N T O M E E T
TOMORROW ’S NEEDS

20
Solving the world’s mega-challenges requires greater
breakthrough innovation, delivered more rapidly. As our authors
explain, delivering breakthroughs requires new approaches,
focusing on using AI and technology to innovate R&D, supporting
people with the structures, organizational models, and optimal
conditions to enable them to become perfect innovators.
Dr. Michaël Kolk, Marten Zieris, Dr. Michael Eiden

THE FUTURE WORKFORCE — RECRUITING AND
R E TA I N I N G V I TA L G E N E R AT I O N Z TA L E N T

34
Generation Z, born between 1997 and 2012, is the first truly digital
native generation, bringing a unique blend of essential skills as
businesses digitize and become more agile. This article explains indepth what Gen Z wants from the world of work, and how companies
can successfully integrate them into the multigenerational workforce.
Lokesh Dadhich, Marten Zieris, Sara Nasaif, Henri Lehmann,
Jérémy Lamri

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ARTHUR D. LITTLEW H Y PAT I E N T C E N T R I C I T Y I S K E Y T O
L O N G -T E R M P H A R M A C O M PA N Y S U C C E S S

48
Despite its role in improving people’s lives, the pharmaceuticalsector hasn’t always put the patient at the center of how
it operates. In an increasingly competitive market, pharmacompanies now have to become more patient centric. From drug
discovery through clinical trials to commercialization, this article
explains why a patient-centric approach is now vital.
Ben van der Schaaf, Ben Enejo, Emmanuel Aisabokhae,
Shreya Modi, Vivien Fergusson

S O F T WA R E R E V O L U T I O N — H O W A I I S
R E S H A P I N G T H E F U T U R E O F S O F T WA R E
PRODUCTS AND SERVICES

62
AI promises to transform the entire software development process,helping both technology businesses and companies that increasingly
rely on digitalization to create competitive advantage. This article looks
at where to focus to drive success — and the pitfalls to avoid.
Bela Virag, Nicholas Johnson, Dr. Michael Eiden, Dr. Michael Opitz,
Riadh Marrakchi, Julian Hartmann, Dr. Christian von Reventlow,
Michael Majster

B E C A R E F U L O U T T H E R E — U N D E R S TA N D I N G T H E
R I S KS O F D E P LOY I N G A R T I F I C I A L I N T E L L I G E N C E

72
As AI usage increases, companies are realizing that alongside the benefits,
it also brings heightened risks. Based on ADL Blue Shift research, thisarticle provides an in-depth explanation of the full range of AI risks,particularly around generative AI, as well as outlining how they can be
managed effectively.
Dr. Albert Meige, Zoe Huczok, Rick Eagar

CEO INTERVIE W: JEREMY NIXON , OCE AN
N E T W O R K E X P R E S S (O N E )86With over 200 vessels in service, Ocean Network Express (ONE) is an
essential part of critical global supply chains. We speak to its CEO,
Jeremy Nixon, who explains the company’s approach to enablingsustainable success and its focus on the human element.
Yumo Ito, Trung Ghi

5

P R I S M : EDITORIALEDITORIAL
DEAR READER

Unless you’re a fan of their music, you might not know that “Human AfterAll” is the title of the third album of electronic music duo Daft Punk.
Its central message, amid a robotic beat, is that despite technologicaladvancement, at the center we remain human beings with all our uniquetalents and vulnerabilities. This is something business executives are
becoming increasingly aware of. Norms and expectations for staff
wellbeing have been changing rapidly, and the explosion of artificial
intelligence (AI) has raised big questions — and concerns — about the roleof humans in the workplace, and indeed, the future of human intelligenceitself. So, we wanted to devote this issue of Prism to ourselves — humans!
A good place to start is to ask the leaders of the world’s biggest
companies. We’re pleased to bring you the results of our 2024 Global CEO
Insights Study, which confirms that CEOs recognize clearly the need tofocus much more on people and skills in an uncertain, AI-transformed
future. Reskilling just moved to the very top of the corporate agenda.
Zeroing in on innovation and R&D, we bring you another groundbreaking
ADL study into the digitally and AI-enabled lab of the future, and wehave a clear conclusion: it’s people centric. It’s all about making people
the best innovators they can possibly be. How well AI is integrated withhuman intelligence — rather than AI itself — will be what determines theworld-beating enterprises of the future.
In 2024, people between 18 and 30 years of age, known as “Gen Z,” will
make up over a quarter of the global workforce. As the first digital native
generation from birth, having grown up in a very different world to that of
the late 20th century, they are not like the rest of us. In our third article,
we explore how organizations can attract and retain this key cohort, so
crucial for the future.
You might think that healthcare is, by definition, human centric,
but in fact, that’s not always the case. Our next article looks at how
pharmaceutical companies can become more patient centric, a growing
determinant of success in a highly competitive marketplace.

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ARTHUR D. LITTLE

Our final articles look at two more important aspects of the AI future.
Firstly, we look at what AI means for the future capabilities of softwaredevelopment organizations, whether in-house or service providers. And
secondly, based on in-depth studies by ADL’s future technology institute,Blue Shift, we address a topic that’s often rather superficially covered: AI
risk. We look at the range of AI risks, and what companies can do to makesure they properly manage their exposure.
To round things off, it’s our pleasure to bring you an exclusive interview
with Jeremy Nixon, CEO of one of the world’s fastest-growing maritime
shipping companies, Singapore-based ONE. Jeremy shares somefascinating insights about how to grow a successful and sustainableglobal business — with a special emphasis on “being very human.”
We hope you enjoy the issue!

Rick Eagar
Chief Editor, Prism
Arthur D. Little

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P R I S M : OP TIMISTIC GLOBAL CEOS FOCUS ON PEOPLE AND
SKILLS IN AN AI FUTURE

OPTIMISTICGLOBAL CEOS

FOCUS ON PEOPLE
AND SKILLS IN AN
AI FUTURE

8

ARTHUR D. LITTLEAUTHORSFrancesco Marsella, Ralf Baron, Petter Killefors,
Maximilian Scherr, Satya Easwaran

Embracing the opportunities that

artificial intelligence (AI) and talent

together can unlock, CEOs are looking
beyond the current instability, andincreasingly confident about the future
prospects for their organizations andthe wider economy. Two-thirds are highly

positive about the global outlook over the
next three to five years, a major increase

from 2023. Given that global tensions haveworsened over the last 12 months, withconflict in the Middle East, disruptions to
Red Sea supply chains, and the continuing
war in Ukraine, this optimism is dramaticand heartening. CEOs understand thatthey have to operate in a volatile,

uncertain, complex, ambiguous world, andbe agile, responsive, and resilient.

Despite the fact that we’re entering an age defined by AI and
automation, people remain crucial to long-term business growth.
That’s one of the key findings of the second global Arthur D. Little
CEO Insights Study. This in-depth research among CEOs fromcompanies with over US $1 billion in revenues finds that as companies
embrace AI, they are investing equally heavily in reskilling theirpeople to maximize its benefits. This picture holds true across thedifferent regions of the world and within the six sectors (telecoms,
energy & utilities, manufacturing, travel & transportation, healthcare,and financial services) that the study covered.
As we’ll explain in this article, they are investing for growth andaiming to develop their people internally to unlock the potential of
AI and drive success. Looking to the future, they want to help shape
the next generation of leaders based on attributes such as ethicalbehavior, sustainability, diversity, and inclusion, and focus on
the customer.

9P R I S M : OP TIMISTIC GLOBAL CEOS FOCUS ON PEOPLE AND
SKILLS IN AN AI FUTURECEOS SEE TECHNOLOGY AS THE
PRIN C IPAL G ROW TH D RIVER IN AN
U N C E R TA I N W O R L D
Technology innovation remains the most critical driver for growth,according to CEOs — a fact that has not changed since 2023. Onequarter of all CEOs listed it as one of the top two most importantfactors, rising to 34% in South America and 29% in North America. This
was ahead of areas such as raw material/energy prices, supply chainpressures, and disruptive competitors.

About the Study
ADL’s 2024 Global CEO Insights Study comprised interviews with
282 CEOs from companies with more than $1 billion in turnover, 39%of whom led businesses with annual revenues of over $10 billion.
CEOs were equally distributed across telecoms, energy & utilities,
manufacturing/automotive, travel & transportation, healthcare, andfinancial services, and based across Europe, Asia, the Middle East,
Africa, and the Americas.

CEOs recognize that the ground rules of business have changed, andthat stable markets that evolve incrementally have gone forever. They
need to operate in an unstable world, with 80% of CEOs expecting
to pay more management attention to volatility, uncertainty,
and related topics over the next three to five years. CEOs aim tocombat this volatility through greater customer focus, closer links
with suppliers, scenario planning, and, most of all, technology andpeople. On the technology side, they are aiming to implement moresophisticated risk management tools, improve business intelligence,increase efficiency, and provide greater flexibility within operations.
“We are making investments in cutting-edge technologies that can
provide us with a competitive advantage in erratic markets.”
CEO, healthcare
Hearteningly, half of CEOs feel that their company has a high levelof readiness to adapt to greater uncertainty, with 16% feeling that
their structures are superior to those of the wider market. This shift
in adaptation is led by larger organizations, of which 28% judge theircapabilities as superior.

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ARTHUR D. LITTLE“We are going to put more effort into becoming more flexible and agile
so that we can react fast to shifting market conditions. This entails
implementing adaptable business strategies and encouraging an
innovative culture.” CEO, financial services

E M P O W E R I N G TA L E N T T O M E E T
CHANGING NEEDS
CEOs agree that the second key element for success in thisenvironment is their people. Here they recognize a need to invest in
training and reskilling to ensure their employees can support theirmore agile operations. On average, 92% of CEOs feel that at least
some reskilling is required for success. Nearly 70% of CEOs from $10
billion+ companies feel that theyHE AR TENIN G LY, HALF O FC EO S FEEL THAT THEIRC O MPANY HAS A HIG H LE VELO F RE AD INES S TO ADAP T TO
G RE ATER UN C ER TAINT Y, WITH
16 % FEELIN G THAT THEIRS TRUC TURES ARE SUPERI O R TO
TH O S E O F THE WIDER MARK E T.

still have a strong or very strong
need to reskill staff to adapt
to a more volatile environment,
compared to just over half of the$1–10 billion turnover group.
Agility has to be led from the top,with CEOs taking a much morehands-on approach to running theirbusinesses. As well as driving fasterchange and improved strategic

decision making, the CEO Insights Study shows that they are focusing
on empowering their people with the right technology, access toknowledge, and relevant skills to create truly agile organizations thatare flexible and responsive to current and future market conditions.

CEOS WELCOME THE RISE OF AI AND ARE
L O O K I N G T O TA P I N T O I T S B E N E F I T S
The record-fast rise of generative AI, and the growing maturity of AI
more generally, offers transformative possibilities (and challenges)
to businesses, whatever sector they are in. As the responses of CEOs
show, in many ways, progress has been swift. Almost all executives
claim to have implemented an AI strategy within at least one
department of their organization. Nearly half say they already have astrategic view of AI across the business.
However, turning vision into reality is more complex. Only 13% ofCEOs have so far adopted a holistic, compelling, and companywide
AI strategy, demonstrating that they are still on a transformation
path to fully understand the impact of AI and integrate it across theorganization. In many ways this is unsurprising — fully benefiting fromAI requires enormous structural and workforce change, which will
only be felt over time. There are major challenges in moving from astrategic view to an actual strategy and then implementing it.

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P R I S M : OP TIMISTIC GLOBAL CEOS FOCUS ON PEOPLE AND
SKILLS IN AN AI FUTURE

The furthest advanced in AI strategy are companies within Asia (75%having a companywide strategy or strategic view), those in financial
services (79%), and $10 billion+ organizations (67%). A clear divide isshown between organizations that feel they are leading their markets,of which 24% have a companywide strategy in place, and laggards,
none of which have implemented such a compelling strategy.

W H AT A R E C E O S U S I N G A I F O R ?
Backing up the fact that organizations are early in their AI
transformation, analysis shows that CEOs are predominantly focusedon using AI to make core functions better by increasing efficiency
and effectiveness, such as through automation. Efficiency andeffectiveness are the leading use cases in the majority of sectors1,
as shown in Figure 1. The sole exceptions are telecoms, travel/transportation, and manufacturing, which are moving beyond
efficiency to use AI to create innovative new business models.
Essentially, while CEOs recognize that AI is disruptive, they also
understand that the real step changes in transforming their businessare yet to come, and that they have work to do to harness AI at a
deeper level.
“We will take advantage of technology, such as artificial intelligenceand data analytics, which can give us real-time insights and support
employees in making wise decisions in dynamic market environments.”
CEO, telecoms

TELECOM

ENERGY &UTILITIESINCREASE
EFFICIENCYFOR COREFUNCTIONS

58

61

47

54

64

66

64

INCREASE
EFFECTIVENESSFOR COREFUNCTIONS

55

56

44

51

59

60

58

IMPROVE
NON-COREFUNCTIONS

47

49

40

45

51

51

50

63

59

50

59

59

57

58

CREATE NEW
BUSINESSMODELS< 50

50 <= x <= 60

MANUFACTURINGTRAVEL &TRANSPORTATIONHEALTHCARE> 60

Note: For this question automotive was split from the overall manufacturing sector, as itprovided radically different results in terms of AI usage.

FIGURE 1: USE OF AI FOR DIFFERENT PERFORMANCE VECTORS PER INDUSTRY (0–100)

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1. For this question automotive was split from the overall manufacturing sector, as it provided
radically different results in terms of AI usage.

FINANCIALSERVICES

AUTOMOTIVEARTHUR D. LITTLE“We are using AI and advanced analytics to find patterns, forecast
trends, and evaluate risks in volatile and complex markets.” CEO,financial services

W H Y A I I N C R E A S E S T H E I M P O R TA N C E
OF HUMANS
AI drives the transformation of the entire organization — its
structures and business models and the markets it operates in. In
order to harness and successfully exploit the potential of AI, CEOs
understand that they require new skills across their workforce.
Reskilling is therefore vital — and needs to be far reaching andtransformative to match changing corporate needs. This is less about
the automatic replacement of humans with AI. Rather, it is about
ensuring that as roles change, employees are equipped to work withand manage AI to thrive in an unpredictable world and deliver on
corporate goals.
“To create more intelligent strategies, we have combined humanexpertise with AI capabilities.” CEO, healthcare
Recognizing this requirement for change, 99% of CEOs see the needfor at least some reskilling, up from 88% in 2023 (see Figure 2). The
scale of the issue has dramatically increased over the last 12 months
thanks to the speed and wide-ranging impact of AI’s rapid rise:– Nearly 60% of CEOs now see a strong or very strong requirement toreskill their employees, up from just 13% in 2023.
– Nearly 60% of manufacturing CEOs see a strong/very strong need toreskill in 2024, compared to 5% in 2023.
– Over 60% of financial services CEOs see a strong/very strong needto retrain their people, compared to 10% in 2023.
“In today’s dynamic and fast-paced business environment, the lesson isto train for adaptability.” CEO, energy & utilities
TO WHAT EXTENT DO YOU NEED TO RESKILL YOUR EMPLOYEES

59%

58%
51%

50%

46%

44%

42%42%

38%

33%

34%

33%

31%
24%
19%

7%
1%
TOTAL

10%

8%
3%

TELCOS

8%

7%

9%

7%

8%

5%

10%

0%

0%

0%

ENERGY & UTILITIESMANUFACTURING(INCL. AUTOMOTIVE)TRAVEL &TRANSPORTATIONNO NEED

LIMITED

MODERATE

STRONG

6%0%
HEALTHCARE

2%

3%

3%

FINANCIAL SERVICES

VERY STRONGFIGURE 2: THE NEED FOR RESKILLING ACROSS SECTORS

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P R I S M : OP TIMISTIC GLOBAL CEOS FOCUS ON PEOPLE AND
SKILLS IN AN AI FUTURE

C H A N G I N G C U LT U R E S T O T H R I V E I N A N
AI WORLD
Alongside investing in training and talent, CEOs understand that theircultures have to transform. They need to be able to attract and retain
talent with the right skills, attitudes, and behaviors to successfully
exploit AI. This requires change, particularly in traditional,
hierarchical businesses in which promotion is linked to length oftenure rather than innate capabilities. Digital natives from Generation
Z are increasingly important. The article “The Future Workforce:
Recruiting and Retaining Vital Generation Z Talent,” elsewhere in thisissue of Prism, provides more details on how to meet their specificrequirements by reshaping processes, cultures, and practices.
“We will increase our investments in employee training anddevelopment, cultivate a favorable workplace atmosphere, and execute
flexible workforce tactics to adjust to evolving business circumstances.”
CEO, healthcare
For global organizations, successfully managing AI and volatility
through traditional, centralized structures is difficult. Instead, newlevels of leaders across the business need to be empowered andtrained to take make decisions in a faster, more informed way, as wellas innovate based on their particular knowledge of specific areas andmarket conditions.
“In order to enable our staff to react swiftly to shifting market
conditions, we will work to provide them greater freedom to makedecisions at their level.” CEO, financial services“We place a high priority on leadership development, skill
enhancement, and employee training in order to produce a highly
competent and flexible workforce that can successfully go throughshifting market conditions and contribute to the success of theorganization.” CEO, telecoms

G R E AT E R F O C U S O N I N T E R N A L TA L E N T
DEVELOPMENT TO BALANCE EXTERNALRECRUITMENT
Previously, CEOs relied heavily on external sources for new
capabilities and talent, primarily headhunters and cooperation with
universities. However, in 2024 this focus has shifted, with the largest
percentage (30%) now looking to internal academies to deliver talentand skills (see Figure 3), up from 21% in 2023.

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ARTHUR D. LITTLE

WHAT ARE YOUR PLANS TO SOURCE NEW CAPABILITIES & TALENT NEEDED FOR GROWTH?

14%

22%

30%

10%

10%

11%

32%

32%

32%

14%

10%
12%
28%

14%

20%

20%

TOTAL

TELCOS

27%

33%

32%

21%

17%

18%

10%

23%

18%

10%

27%

22%

25%

17%

MANUFACTURING(INCL. AUTOMOTIVE)

INTERNAL ACADEMY

19%

29%

25%

ENERGY & UTILITIESCOOPERATION WITH UNIVERSITIES AND ACADEMIA

10%

11%

TRAVEL &TRANSPORTATIONHEALTHCAREFINANCIAL SERVICESCORPORATE VENTURE CAPITALACQUISITIONSHEADHUNTERS

FIGURE 3: WHERE CEOS PLAN TO SOURCE NEW TALENT AND CAPABILITIESThis increasingly balanced view is driven by multiple factors, including
the difficulty of finding AI talent given global skills shortages, a needto retain existing high-achieving talent and experience, and a growing
realization that technical knowledge needs to be married to businessunderstanding to deliver effective results tailored to the specificcompany and its objectives.
CEOs see developing their own people as delivering faster results,
as new skills such as AI can be layered on their existing expertise,
without the requirement to train new

C EO S S EE DE VELO PIN G THEIROWN PEO PLE AS DELIVERIN G
FAS TER RESULT S , AS NE W
S K ILL S SUC H AS AI CAN BE
L AYERED O N THEIR E X IS TIN G
E X PER TIS E .

joiners on company operations fromscratch. Internal academies also
support the growing focus on lifelong
learning that staff (particularly
Generation Z or Millennials) aredemanding from their employers.
These employees also increasingly
want to work for companies that share

their sense of purpose and values, particularly around ESG, somethingthat CEOs recognize and are acting on.
“We are gaining the trust of our staff members by being transparent
about the company’s objectives, difficulties, and decision making
procedures.” CEO, manufacturing
While the majority of sectors are taking a balanced approach to
future talent, variations are shown between sectors. CEOs in thetelecoms, manufacturing, travel & transportation, and healthcare
sectors are the most enthusiastic about internal academies, while
healthcare organizations are also increasing their focus on building
talent through acquisition, at the expense of traditional cooperation
with universities and academia. Energy & utilities CEOs also aim to
primarily source new talent via acquisition, while financial services
are looking to corporate venture capital, investing in fintechs to plug
their skills gaps. Travel & transportation is the only sector to increase(slightly) its reliance on headhunters, although they are seen as anintegral part of the recruitment mix in most sectors.

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P R I S M : OP TIMISTIC GLOBAL CEOS FOCUS ON PEOPLE AND
SKILLS IN AN AI FUTURE

C R E AT I N G T H E N E X T G E N E R AT I O N
OF LEADERS
What are the skills that CEOs need for the future? To find out, CEOs
were also asked for leadership advice they’d provide to younger
generations, based on their own experiences and how the businessworld is changing. Five themes stood out:
1. F
 ocusing on sustainability and social issues, including diversityand digital inclusion
2. Behaving ethically and morally at all times and demonstrating thecompany purpose, reinforced by strong governance processes
3. Being flexible, adaptable, and entrepreneurial, and not
fearing failure
4. Putting the customer first and continually listening to their needs
5. Embracing lifelong learning, staying curious, and having acommitment to gaining new skills while supporting/mentoring
the next generation“Within your company, promote inclusion and diversity. Encourage anenvironment where people with different experiences, viewpoints, andbackgrounds are valued at work.” CEO, utilities
This demonstrates that today’s CEOs are fully aware that they need tohave a radically different vision of what success involves than thoseof the past. They are moving well beyond revenues and market sharetoward achieving a better balance between financial metrics andethical/environmental factors, essentially aiming to leave the world(and their companies) in a better place when they move on fromtheir roles.
“Encourage creativity and a willingness to explore novel concepts.
A firm with an entrepreneurial atmosphere might be able to develop
business strategies that give it an edge over competitors in volatile
markets.” CEO, automotive

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ARTHUR D. LITTLE

INSIGHTS FOR THE EXECUTIVE
Overall, the 2024 CEO Insights Study clearly shows that seniorbusiness leaders of the world’s biggest companies are optimistic
about the future and focusing on AI and human skills to achieve theirsustainable growth objectives.

1. EMBR ACE R ADICAL CHANGE
THROUGH AI
CEOs have ambitious plans for technology, particularly AI. This has
the potential to transform their entire business, but they need totranslate their plans and strategies into concrete, companywide
programs. Currently, many AI use cases focus on making existingprocesses more efficient and effective — CEOs need to go beyond
this to deploy AI to innovate and target new opportunities to reap
maximum benefit and competitive advantage. They need to embrace
the transformative changes to their business models that AI enables,
opening new markets, opportunities, and partnerships.

2 . K E E P P A C E W I T H I N N O V AT I O N
The rapid rise of AI demonstrates how quickly new technologies canmove from the periphery into the mainstream. CEOs must therefore

THE R APID RIS E O F AI
DEM O NS TR ATES H OW Q UIC K LY
NE W TEC HN O LO G IES CANM OVE FRO M THE PERIPHERY
INTO THE MAINS TRE AM .

keep a watch on other breakthroughtechnologies, such as quantum
computing and autonomousvehicles, monitoring progress andunderstanding how they might
impact their business once
they mature.

3 . U N D E R S TA N D T H AT A I P L U S H U M A N
S K I L L S M A X I M I Z E S R E S U LT S
Even the most powerful AI tools won’t deliver impact if they are not
adopted across the company. To democratize AI, ensure that tools areavailable and usable by relevant parts of the workforce. By supporting
people with AI, you can improve their performance — and that of thewider company.

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P R I S M : OP TIMISTIC GLOBAL CEOS FOCUS ON PEOPLE AND
SKILLS IN AN AI FUTURE

4 . C O N C E N T R AT E O N I N T E R N A L
P E O P L E , S K I L L S , A N D C A PA B I L I T I E S
Ensure that companies have the right internal skills and capabilities
to deliver an ambidextrous, agile learning organization. This relies
on fundamental reskilling of the workforce to ensure they havethe correct talent mix to

THE S K ILL S AND AT TRIBUTESO F A SUC C ES S FUL C EO HAVES HIF TED — WITH A NEED TO
BAL AN C E PRO FITAB ILIT Y
AND FINAN C IAL SUC C ES S
WITH E THICAL , SUS TAINABLE
BEHAVI O R .

drive the business forward.
CEOs must therefore focus
heavily on ensuring they
have access to these skills
across the business throughinternal programs/academies,
cultural change to support
the shift to lifelong learning,and communication/change
management to inform,

educate, and engage staff at a time of disruption. Given skills
shortages around AI, attracting talent and reskilling may require
unconventional approaches, from creating standalone AI subsidiaries
to companywide AI training programs.

5 . C R E AT E T H E N E X T G E N E R AT I O N
OF LEADERS
The skills and attributes of a successful CEO have shifted — witha need to balance profitability and financial success with ethical,
sustainable behavior. Today’s CEOs should look to nurture the next
generation of leaders, providing them with support and mentorshipto develop their talents for the future.

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ARTHUR D. LITTLEFRANCESCO MARSELLA
is a Managing Partner in Arthur D. Little’s Rome office
and responsible for leading the company’s Growth andTransformation practices worldwide.
RALF BARON
is a Partner in Arthur D. Little’s Frankfurt office and amember of the Transformation practice.
PETTER KILEFORS
is a Managing Partner in Arthur D. Little’s Stockholm
office, leading the company in the Nordics, and amember of the Growth practice.
MAXIMILIAN SCHERR
is a Partner in Arthur D. Little’s Vienna office, where
he leads the Growth and Performance practices.
SATYA EASWARAN
is a Partner in Arthur D. Little’s India office and amember of the Growth practice.

19

P R I S M : THE PEOPLE-CENTRIC LAB OF THE FUTURE —AI-SUPPORTED INNOVATION TO MEET TOMORROW’S NEEDS

THE PEOPLE-CENTRICLAB OF THE FUTURE

AI-SUPPORTED INNOVATIONTO MEET TOMORROW’S NEEDSARTHUR D. LITTLEAUTHORS
Dr. Michaël Kolk, Marten Zieris, Dr. Michael Eiden

As the world grapples with global megachallenges, innovation1 has never been

more necessary. We need breakthroughinnovation to solve pressing issues

around energy, the environment, andsocial and health challenges. At thesame time, and equally importantly,

companies have to deal with a businessworld typified by increased complexity

and accelerated time frames. Together
these mean innovation must deliver

more breakthroughs, rather than only

incremental improvements, with more
flexibility and responsiveness and at
greater speed.

However, these breakthrough innovations require new approaches
that go beyond traditional ways of working. Our research in the
Global Innovation Excellence Benchmark 2 shows that more than
80% of companies are unsatisfied with their return on breakthroughinnovation investments. Many CEOs and CTOs that we speak to
say their innovation pipeline isn’t nearly enough to support theircompany’s growth ambitions.
In “The Laboratory of the Future,”3 our 2020 Prism article, we argued
for the need to take a new, people-centric approach to digitalized
R&D (by “lab,” we mean the entire “delivery engine” of R&D). We madethe point that to meet the challenges of increasing convergence, as
well as the need for more and more rapid breakthroughs, the lab had
to be designed around people, rather than technologies or systems.

1. In this article we will use the words “innovation” and “R&D” more or less interchangeably. With the former we
imply a broader concept of which R&D can be considered an integral part2. 9th Arthur D. Little Global Innovation Excellence Benchmark, June 2023
https://www.adlittle.com/uk-en/insights/report/good-great-enhancing-innovation-performance-through-effective-management-processes
3. “The Laboratory of the Future,” Prism S1 2020
https://www.adlittle.com/uk-en/insights/prism/laboratory-future21

P R I S M : THE PEOPLE-CENTRIC LAB OF THE FUTURE —AI-SUPPORTED INNOVATION TO MEET TOMORROW’S NEEDS

Since then, the sudden acceleration of artificial intelligence (AI) has
started to transform how we do business, with innovation and R&D
being no exception. Hardly a week goes by without the announcementof yet another fascinating AI use case — one example is “Coscientist,”an AI-driven approach that combines different GPT-4 models andis capable of designing, planning, and executing experiments in thecontext of chemical research4. A second, equally fascinating example
is “FunSearch,” an AI approach that combines a large language model(LLM) with an evaluator module in the search for novel solutions toopen problems in the world of mathematics5.
While these two examples are fairly specialist and mostly driven byacademic research groups, the broader potential of AI to transform
innovation and R&D is huge. We can already see the effect thatgenerative AI is having

IT WILL TAK E YE ARS O R E VEN
DECADES BEFO RE C O MPANIESAND INDUS TRY S TANDARDSWILL HAVE C O NVERG ED
TOWARD ANY S IN G LE “ BES TPR AC TIC E” IN IT S US E .

on access to anddemocratization ofknowledge. AI is rapidly
becoming a generalpurpose technology
with enormous potential
impact, akin to the adventof electricity and theinternet in the 19th and20th centuries, respectively, when entire business sectors weretransformed forever and fortunes were made by early vendors
and adopters.
However, it will take years or even decades before companies andindustry standards will have converged toward any single “bestpractice” in its use. Such future standards will also need to addressconcerns such as (cyber)security, accuracy, and “explainability.”
These are not the main topic of this article, but certainly important
to consider 6.
In the meantime, the companies that are most adept at identifying,accessing, and broadly deploying leading AI technology and use
cases within R&D will see enormous benefits. This article considers
the “big ticket” potential of AI to innovate how innovation is done.
In particular, we will explore the importance of putting people atthe heart of AI-augmented innovation, supporting them with thestructures, organizational models, and optimal conditions to enable
them to become perfect innovators, uniquely placed to bring the
breakthrough innovations that the world is waiting for.

4. https://www.nature.com/articles/s41586-023-06792-0
5. https://www.nature.com/articles/s41586-023-06924-6

22

6. See “Be Careful Out There — Understanding the Risks of Deploying Artificial
Intelligence” elsewhere in this issue.

ARTHUR D. LITTLE

H O W A I C A N H E L P I N N O VAT E H O W
I N N O VAT I O N I S D O N E
The list of challenges to creating a steady stream of breakthroughinnovations is long and potentially dispiriting. Success rates are
low, with lead times often excruciatingly long and the ability ofcompanies to realize the full potential of successful technology
breakthroughs low.
So how could AI change this picture? Examples of successful AI
applications in R&D are already plentiful. Uses range from ideationand literature-based discovery; through novel concept creation andin silico design and experimentation, rapid candidate screening in
drug discovery, trend analysis, and pattern recognition; to prototype
development, design optimization, and testing support. Multiple
LLMs can be bundled and/or combined with other systems and APIs
to support almost any task a human researcher would undertake. AI
use is greatly bolstered by the fact that it is able to “read” almost any
type of unstructured information in a multimodal fashion, such ascomplex tables, charts, and drawings.
Progress will not stop there. Based on generative AI’s sevenarchetypes of human intelligence7, we expect innovation teams toprimarily benefit from using AI in these typical roles:– Scribe: generating content across all media, based on
specific prompts– Librarian: answering questions, lookup, and search– Analyst: summarizing data series and underpinning patternrecognition and extrapolation– Engineer: aiding task definition, analysis, and optimization
for problem solving– Scientist: causal inference of general laws based on empiricalobservation and counterfactual reasoning– Craftsman: directing and manipulating physical tools and objects
in uncontrolled environments– Artist: aiding ideation and design, bringing together diverse
influences and perspectives to help innovators create originalideas and concepts
While it is easy to see how these AI applications could increase
innovation productivity and efficiency, if they are simply plugged into
a “traditional” lab setting, they won’t in themselves bring about thetransformation needed to meet today’s and tomorrow’s needs. For
the foreseeable future at least, AI will be a copilot or assistant to thehuman beings running the lab. To get the most out of AI, innovation
and R&D organizations need to focus on people.

7. “Generative Artificial Intelligence: Toward a New Civilization?” Blue Shift Report, October 2023
https://www.adlittle.com/en/insights/report/generative-artificial-intelligence-toward-new-civilization

23

P R I S M : THE PEOPLE-CENTRIC LAB OF THE FUTURE —AI-SUPPORTED INNOVATION TO MEET TOMORROW’S NEEDSB U I L D I N G T H E L A B O R AT O R Y O F T H E
FUTURE — PEOPLE BEFORE TECHNOLOGY
The lab of the future is the target destination for any largeorganization aspiring to break out of the traditional R&D mold. At
its core, it aims to make people into “perfect innovators” to realize
strategic objectives, akin to automatic driving aids aiming to makepeople into “perfect drivers.” This is about much more than offering
technology and hoping for the best. Instead, it means re-engineering
a fully people-centric lab approach, enabled by AI and other digital
tools, based around three key components: democratization,
collaboration, and ambidexterity (see Figure 1).

EMPOWERING PEOPLE TO INNOVATEUSING AI AND TECHNOLOGY TO ENHANCE PERSONALMASTERY OF DATA AND KNOWLEDGE

PEOPLE-CENTRICLAB OFTHE FUTURE

ORGANIZING PEOPLE
TO INNOVATESTRUCTURE, GOVERNANCE, AND CULTURE
TO REMOVE BARRIERS TO AI-ENABLED
BREAKTHROUGHSCONNECTING PEOPLE
TO INNOVATEUSING AI AND TECHNOLOGY TO
BUILD AND STRENGTHENDATA AND KNOWLEDGE ECOSYSTEMSFIGURE 1: THE AI-ENABLED, PEOPLE-CENTRIC LAB OF THE FUTURE

In essence, the concept is straightforward:– Democratization involves making AI available, customized foreveryone and adopted as a natural way of working, closing the gap
between AI users and AI providers.
– C ollaboration involves using AI and other digital tools to help
supercharge the sharing of data and knowledge, forming avirtuous circle unconstrained by the limitations of current data
management.
– Ambidexterity involves setting the organizational context tofacilitate and encourage AI-supported breakthrough innovation andexploration, at the same time as maintaining R&D efficiency andproductivity.

24

ARTHUR D. LITTLE

While these three components can be considered separately, they
are connected and mutually reinforcing: democratization requires
pervasive sharing of data and knowledge, which, in turn, requiresorganizational ambidexterity, and so on.

D E M O C R AT I Z AT I O N
In 2023, access to and interaction with powerful AI systems such as
LLMs became democratized. For example, advances in reinforcement
learning through human feedback (RLHF) have enabled easy
conversational access to these very powerful models for everyone. AI
usage is no longer exclusive to very large companies, but has become
available to the wider world. The fact that Open AI’s ChatGPT model
managed to attract more than 175 million users in one year is a clear
testament to this.
When considering AI’s potential through a people-centric lens, it
helps to start by defining what makes people, and innovators inparticular, truly good at their job. The T-shape (see Figure 2) has
often been used as a model to represent a person’s specific areas ofexpertise (vertical), as well as more interdisciplinary collaboration
skills (horizontal). The same model can be applied to the AI models
and bots required to support people in their daily jobs (as highlighted
in a previous Prism article8).

KNOWLEDGE
INTEGRATION• INTELLIGENCE• COLLABORATION• LEARNING• SYSTEM
ENGINEERINGKNOWLEDGE
EXPANSION• PREDICTION• EXPERIMENTALDESIGN• PROBLEM SOLVING• DESIGN THINKING

FIGURE 2: THE T-SHAPED POWER OF AI-EMPOWERED R&DAI, when integrated into researchers’ natural ways of working,can unlock the promise of complete knowledge integration, in
combination with step changes in the pace and reach of knowledge
expansion. This is key to developing broader technology portfolios,
greater technology advances, more breakthrough and business model
innovations, shorter time to market, and the ability to address
larger markets.

8. “Taking Control of AI,” Prism S2 2023
https://www.adlittle.com/sites/default/files/prism/ADL_PRISM_S2_2023_Taking%20control%20of%20AI.pdf

25

P R I S M : THE PEOPLE-CENTRIC LAB OF THE FUTURE —AI-SUPPORTED INNOVATION TO MEET TOMORROW’S NEEDSAI can be applied to enhance knowledge integration in several
ways, for example:– Accelerating solution engineering: Thanks to AI, the ability toaccess and synthesize sources for insights becomes potentiallylimitless. Transversal solution design skills determine the ultimate
impact of solution engineering. For example, General Motors
reports that it is combining generative AI, working mainly in thecraftsman role, with additive manufacturing to drastically extend
the design space to be explored for novel parts and components.
– Enabling co-creation: AI can fulfill the role of analyst and engineer
in co-creation with humans, especially in systems engineering,which requires the involvement of multiple stakeholders, manyof which are non-technical, such as in model-based systems
engineering. Smart cities are one example of this type of
application.
– Blending of formal and informal knowledge streams: AI canhelp spark ideation and increase problem solving by integrating
formal and informal knowledge streams. While formal knowledge
is already encoded in data (being structured or unstructured
in nature), informal/tacit knowledge can be inferred throughinteraction patterns. For example, this could be facilitated throughtranscription of brainstorming sessions or using a generative AI
model as a “sparring partner” in ideation processes. The greater
knowledge transparency provided through AI helps with innovation
decision making: for example, direction setting (where to look),priority setting (where to go deeper), and opportunity validation(where to develop).
Turning to knowledge expansion, AI can also help in multiple ways,
for example:– Hyperspecialized learning: Creating specialized and highly
personalized AI models (working as scribe and librarian) will
accelerate learning on subject matter expertise, increasing
the scale and spread of critical knowledge pockets. The almost
personal nature of these

THE G RE ATER K N OWLED G E
TR ANS PAREN CY PROVIDED
THRO UG H AI HELP S WITHINN OVATI O N DEC IS I O N
MAK IN G .

LLMs will most likely meanthat they will be able to run
on end user devices and bereadily available whenevera user wishes to interact
with them. A recent paper
published by researchers fromApple9 highlights a novel approach to running LLMs for inference on
low-powered edge devices. This will most likely mean we will have apersonal GPT available on our iPhones in the near future.

26

9. https://arxiv.org/pdf/2312.11514.pdf

ARTHUR D. LITTLE– Augmentation of project teams: AI’s predictive capabilities
greatly improve the effectiveness and speed of experimentation.
Generative AI routinely fulfills the role of engineer and scientist,
augmenting increasingly complex human tasks. This evolution
toward hybrid ecosystems (of subject matter experts and bots) will
require dedicated leadership, as well as continuous development
and maintenance, to remain effective. The “Coscientist” approach
recently published by researchers at Carnegie Mellon University
is a great example of this. They have combined several LLMs forproblem solving, code generation, and experimental design, withthe ultimate goal of accelerating R&D in chemical research.
– Fluidity of problem solving approaches: Librarian-like AI
will vastly increase the visibility of alternative approaches andtechnologies to overcome technical hurdles, for instance, byfinding solutions to similar problems in unrelated industries. This
will have significant implications for project team composition andmentality. The application of generative AI approaches to wellestablished problem solving frameworks, such as TRIZ, could create
significant productivity gains in this domain.
Across both dimensions, the design and interface of AI tools isvital if they are to achieve widespread user adoption, and thus deliver
benefits. They have to be integrated within existing ways of working
that staff are comfortable with and augment their capabilities. For
instance, one of our clients (a large chemical player) has developed
a transversal LLM team to support both “horizontal” and “vertical”
initiatives across its vast R&D community.

C O L L A B O R AT I O N
The limitations of current collaborative data sharing and knowledge
management systems have been amply described. Put simply, criticalknowledge and data are often not accessed and used because they:– Are not properly codified/tagged– Sit in inaccessible locations– E xist in different file formats and/or different languages– Are “tacit” (i.e., part of people’s professional experience)– Are spread across multiple different ecosystem players– Are not being sought or shared by individuals for a varietyof reasons

27

P R I S M : THE PEOPLE-CENTRIC LAB OF THE FUTURE —AI-SUPPORTED INNOVATION TO MEET TOMORROW’S NEEDS

These obstacles are significant for deploying AI to help create perfectinnovators because AI needs data by the truckload and people need
new knowledge and insights to make new discoveries. Fortunately, AI
and other digital tools are also part of the solution, for example:– Advanced knowledge search: LLMs can be combined withknowledge graphs and vector databases to create new solutions
that combine natural language processing with content andcontextual search. ADL has recently deployed this type of tool for
its own internal use.
– Intelligent triggers: AI tools can be applied to provide prompts toinitiate the transfer of information or catalyze learning activities.
Examples include predicting users’ future needs and prompting
action, providing tailored knowledge debrief protocols at key
milestones, and automating translation and tagging to generate
quick reference lists for specific topics.
– K nowledge management aids: AI can support documentation,
search, transfer, and learning. For example, generative AI cansuggest non-obvious and/or lateral information in searches andgenerate new content from unstructured data (such as text/video/
audio) for knowledge capture. Graph data technology makes it
simpler to identify previously hidden relationships within vast
amounts of textual data within repositories.
– User experience enhancement: New tools can be deployed
to make interfaces easier to use than not to use. For example,
adoption engineering can be employed to make sure knowledge
management and learning solutions “go viral” and deliver behavioral
change with seekers, while gamification encourages owners toshare information. Within repositories, powerful data visualizationinterfaces make understanding and prioritizing information easier.

AMBIDEXTERITY
While simply applying AI technology and tools to an existing lab
structure has already had benefits, it is unlikely to result in any major
breakthroughs (or even smaller ones) unless necessary changes arealso made to the wider organizational context and operating model.
After all, why would AI-enabled breakthroughs sail by well-known
obstacles that plague other types of breakthrough innovations, suchas inept decision making and misaligned incentives?
The lab of the future needs to embrace ambidexterity, balancing
optimal exploitation of today’s innovation space and explorationof tomorrow’s growth domains — indeed, this why the T-profile ofknowledge integration and knowledge expansion is essential.
R&D organizations that are geared toward exploitation tend to
apply standardized formal structures and processes, supported bya performance-driven culture with KPIs focused on efficiency, cost
reduction, scale, and productivity.

28

ARTHUR D. LITTLE

Those that are focused on exploration tend to have more lateraland fluid structures to allow greater responsiveness (for example,
based on communities of expertise or guilds). Processes follow agile
thinking and focus on iteration, rapid validation of ideas/sparks, andmore freedom to follow “big bet”

ADL’ S “AMB IDE X TRO USO RGANIZ ATIO N AS S ES S MENTDATABAS E” FINDS THAT O NLY
15% O F C O MPANIES ARE FULLYAMB IDE X TRO US , WITH THE
MA JO RIT Y (5 5%) O P TIMIZEDFO R E X PLO ITATI O N (SCALE
AND PRO DUC TIVIT Y ) .

projects. Steering and incentives
are more rooted in purpose anddirection setting than individual
project control.
Most R&D organizations, inpractice, lean toward one ofthese archetypes or the other.
ADL’s “Ambidextrous Organization
Assessment database” findsthat only 15% of companies are
fully ambidextrous, with the

majority (55%) optimized for exploitation (scale and productivity). A
large majority of industrial R&D organizations still need to achieve
ambidexterity, yet without it, the full potential of AI is unlikely tobe realized.
So, what are the key features of ambidexterity in practice? Apple
provides some useful pointers.

LESSONS LEARNED FROM APPLEIN AMBIDEXTERITYApple is a longstanding innovation leader. We recently benchmarked
Apple’s R&D function through interviews and desk analysis, confirming
the importance of ambidexterity to its success. Notable features of
its practices include the following:– Ambidexterity in decision making and performance

management: Decision making depends on the type of project:more belief-based for design initiatives versus hard data to drive
technical hardware specs. The steering of individual projects ismuch more closely linked to the ambitions and expectations ofleaders (see next point) than dedicated KPIs, with team reputation
seen as a more effective “control mechanism” than fixed indicators.
R&D employee incentives are usually based on overall company
performance rather than individual projects/products.

– Ambidexterity in people management: Leaders are required tobalance deep expertise and immersion in details with willingness
to collaborate, with staff continuously assessed on these criteria.
Apple follows the “experts lead experts” rule, requiring leaders toconstantly learn in new areas as they become relevant to their areaof responsibility. Clear distinctions have been made between topics
to own, delegate, learn, and teach.

29

P R I S M : THE PEOPLE-CENTRIC LAB OF THE FUTURE —AI-SUPPORTED INNOVATION TO MEET TOMORROW’S NEEDS– Ambidexterity in structure: Despite its size, Apple is purposely
following a functional, rather than project-based, organizationalmodel. In combination with other practices, it uses an expertisedriven approach and reduces the number of executives involved
in decision making. While it still adopts project-driven ways ofworking, rather than fully formalizing this through organizational
structures, it places much emphasis on a few selected project
leadership roles, which are taken very seriously.
Comparing Apple R&D to a typical industrial company shows majordifferences in the ambidexterity balance (see Figure 3).

EXPLOIT

100%“EXPLOIT”

100%“EXPLORE”

EXAMPLEEXPLORE

100%“AMBIDEXTROUS”

STEERING &TRANSFORMATIONPEOPLE &CULTURER&D AT APPLESTRUCTURE &PROCESSR&D AT AN INDUSTRIAL COMPANY

FIGURE 3: AMBIDEXTERITY COMPARISON OF R&D ORGANIZATIONS AT
APPLE AND A TYPICAL INDUSTRIAL COMPANY (ADL CLIENT BENCHMARK)

Two findings stick out from the comparison. First, whereas AppleR&D has embedded both “explore” and “exploit” in all organizational
dimensions, industrial companies tend to optimize for “exploit”
following predictable and well-controlled practices. Second, manyindustrial R&D organizations have dedicated units, and sometimes
locations, designed for breakthrough innovation (“explore”), but
this does not seem to be Apple’s formula for breakthrough success,which instead resides more in its whole approach to steering andtransformation and managing people and culture.
Finally, Apple also exhibits the other key characteristics of thepeople-centric lab of the future, which we have already discussed.
AI democratization and leadership are fully embedded within its
functional organization as key guiding principles:

30

ARTHUR D. LITTLE– Democratization: A distributed (democratized) approach to AI
classifies it as a crucial skill and requires the broader leadership toreach critical skill levels. It has no separation between “innovatingwith AI” (for example, increasing R&D productivity) and “innovations
with AI” (such as improving the Siri functionality of iPhones).
– C ollaboration: Apple embraces its knowledge ecosystem, withhigh permeability in terms of AI experts moving in and out of thecompany routinely. It relies heavily on a managed ecosystem of hightech and software companies, academia, and startups.

INSIGHTS FOR THE EXECUTIVE
The scope and potential of the AI-driven, people-centric lab of
the future is enormous. Resources are always limited and often
spread thinly, which makes prioritizing (what is most important) andphasing (what do we do first) according to what matters most for thecompany’s strategic objectives crucial.
The guiding principle is “build for advantage, buy for parity”:
focus efforts on must-win innovation battles based on superior
technical capabilities, while adopting proven best practices andcommercially available solutions for less important topics. For
example, a pharmaceutical company may decide to deploy AI mainly
to supercharge its core R&D activity of new drug discovery, while afood ingredient company might focus on AI-enhanced digital services
around personalized nutrition and formulation. The principle is thesame, but the focus is different.
These strategic innovation priorities can then be mapped to theT-shape model presented in this article: what are the implications to
AI-driven knowledge integration and expansion? Do not get bogged
down in technologies at this stage, but instead concentrate on what
would need to happen along these two dimensions to make yourpeople into “perfect innovators.”
This will give you the solution promises of AI that are specific to yourcompany, which, in turn, will define the blueprint for your peoplecentric lab of the future. Focus on developing the three
key components:

1 . D E M O C R AT I Z AT I O N– Identify and prioritize AI use cases and adoption, integrated acrossthe R&D and innovation cycle, with defined AI skill-level targets andcompetences.
– Focus on end-to-end processes so technical experts can seamlessly
adopt AI into their working routines.
– Ensure no separation between “innovating with AI” and “innovations
with AI.”

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P R I S M : THE PEOPLE-CENTRIC LAB OF THE FUTURE —AI-SUPPORTED INNOVATION TO MEET TOMORROW’S NEEDS

2 . C O L L A B O R AT I O N– Develop and build out future requirements in terms of dataarchitecture and engineering, as well as user experience.
– S trengthen and diversify the wider innovation ecosystem andincrease permeability between roles, teams, and the company
at large.
– Redefine the skills and expertise that are needed and use this todrive hiring, training, and team composition.

3. AMBIDEXTERITY– S trengthen the role and caliber of project leadership and solution
engineering and increase the iteration steps in end-to-end
innovation with more frequent optimization.
– Focus on optimized decision making — reduce hierarchies andredesign governance to differentiate between types of decisions.
– Foster an innovation culture that is familiar and comfortable withuncertainty and ambiguity — essential for being able to experimentand learn along the AI adoption journey.
AI is often portrayed in the popular media as a threat to people,
threatening to take over their jobs and make them surplus torequirements. While the far future is impossible to predict, in the
coming years at least, AI is paradoxically one of the most powerfultools we have to put people back at the center of industrial
enterprise, where they belong.

32

.

ARTHUR D. LITTLE

DR. MICHAËL KOLK
is a Managing Partner in Arthur D. Little’s Amsterdam
office and responsible for leading the company’s
Innovation practice worldwide.
MARTEN ZIERIS
is a Partner in Arthur D. Little’s Frankfurt office and amember of the Transformation practice.
DR. MICHAEL EIDEN
is a Partner in Arthur D. Little’s London office and amember of the Innovation practice.

33

PRISM: TSH
I MEUFLUATT UI NRG
E W
S TORRATK FEOGYR C–E T—
H ER ERCER
AU
L IP
T IONTGE N
AT
NID
A LR EOTAF INING
TH
V
I TA
E L
I NGDEUNSETRRATIALI OM
NEZTAV
TAE
LR
ES
NET

THE FUTURE
WORKFORCERECRUITING AND RETAINING
VITAL GENERATION Z TALENT
34

ARTHUR D. LITTLEAUTHORS
Lokesh Dadhich, Marten Zieris, Sara Nasaif, Henri Lehmann, Jérémy Lamri

Generation Z (widely known as Gen Z),

encompassing those born between 1997

and 2012, is anticipated to make up over
one-quarter of the global workforce by2025, according to the World Economic
Forum. As the first digitally nativeand globally connected generation,
Gen Z brings distinctive skills andcapabilities to organizations, making

their recruitment and retention essential
for sustained business success in the eraof digital transformation and artificial
intelligence (AI). This is especiallysignificant for companies within

traditional industrial sectors grapplingwith the challenges of digitization,
striving to achieve ambidexterityby balancing agility and innovation

with existing strengths in scale andproductivity.

Nevertheless, the growing presence of Gen Z in the workforce
comes with its own set of challenges. Gen Z as a whole possesses
unique needs, expectations, and motivations, diverging from their
immediate predecessors in Generation Y, commonly known as
Millennials. Surprisingly, our research shows that only 26% of Gen Z
individuals feel that current jobs align with their values. Effecting atransition toward Gen Z compatibility within organizations, without
estranging current employees, demands transformative change andreconfiguration of management styles and structures.

35

P R I S M : T H E F U T U R E W O R K F O R C E — R E C R U I T I N G A N D R E TA I N I N G
V I TA L G E N E R AT I O N Z TA L E N T

Based on surveys of Gen Zers in North America, Europe, Southeast
Asia, and the Middle East, as well as interviews with Global HR
directors, this article outlines the essential measures organizations
must undertake in terms of mission, structure, and culture toeffectively harness the invaluable skills of their newest recruits.

U N D E R S TA N D I N G G E N E R AT I O N Z
GENERATIONZGENERATIONYGENERATIONXBABYBOOMERSSILENT
GENERATIONGREATESTGENERATION

1900

1920

1940

1960

1980

2000

FIGURE 1: GENERATIONS BY YEAR OF BIRTHGen Z stands out as the first generation to grow up entirely in thedigital era, devoid of any recollection of a world before the internet(see Figure 1). Unlike their Millennial counterparts, who embraced theinternet later, in their developmental years, Gen Z members are genuine
digital natives, having been immersed in technology since birth.

W H AT S E T S G E N Z A P A R T ?
While acknowledging the risks associated with generalizations,
we note several key traits and characteristics commonly observed
among Gen Z individuals:– Tech prowess: Proficient in the use of technology, they perceive it
as an inherent aspect of their surroundings, rather than a skill tobe acquired.
– Global perspective: The omnipresence of social media hassignificantly shaped Gen Z’s worldview. Exposure to a constantinflux of information around the clock via platforms such as
Instagram and X (formerly Twitter) has not only made them globally
aware, but also influenced their perceptions of life, environmental
issues, ethics, and standards of work and work-life balance. Social
media serves as a powerful lens through which they interpret andengage with the world.
– Challenging socioeconomic experiences: Many Gen Z individuals
have witnessed the repercussions of the 2008 recession on theirfamilies, faced disruptions in education and early career steps
because of the COVID-19 pandemic, and are currently contending

36

2020

ARTHUR D. LITTLE

with soaring housing costs. These issues are adversely affecting
their mental health, with 42% diagnosed with specific conditions.
For some Gen Zers, this has led to loss of trust in establishedpolitical and institutional structures.
– Diversity: Gen Z exemplifies a rich tapestry of backgrounds, withnearly half of its members in the US representing racial or ethnic
minorities, as indicated by census data. This demographic intricacy
is a testament to the profound impact of globalization, which has
shaped Gen Z as products of increasingly heterogeneous societies
or melting pots. Additionally, their heightened inclination towardpursuing higher education distinguishes them from preceding
generations.
These factors all contribute to the formation of values that Gen
Z holds dear. Their advocacy for inclusivity, diversity, and social
responsibility stems from their unique experiences, coupled witha profound need for purpose in both personal and professional
spheres. The omnipresence of social media leads to amplificationof their opinions on a wide array of subjects, as well as greater
active engagement. Consequently, this can create an impressionof heightened knowledge and maturity, even among the youngest
members of this cohort.

Comparing Generations in the Workplace
Organizations today boast diverse workforces spanning multiple
generations, each characterized by unique attributes anddistinct expectations:– Baby Boomers (1946–1964): Anchored in a desire for security, Baby
Boomers favor hierarchical structures and often subscribe to a “liveto work” ethos. Many have devoted their entire professional lives toa single employer.
– G eneration X (1965–1980): Thriving in collaborative environments,
Generation X appreciates teamwork while maintaining a selfeffacing demeanor. Respect for their work is paramount, and they
prefer autonomy without the constraints of micromanagement.
– G eneration Y (1981–1996): Driven by a quest for purpose,
Generation Y (Millennials) seek meaning in the organizations
they align with. They actively seek continuous feedback on theirperformance, emphasizing a dynamic exchange in the workplace.
– G eneration Z (1997–2012): Prioritizing mental health support,
Generation Z shares with Millennials a desire to work for companies
infused with a sense of purpose and the flexibility to adapt tovarying work arrangements. Notably, financial rewards hold greater
significance for Generation Z than their Millennial counterparts.

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P R I S M : T H E F U T U R E W O R K F O R C E — R E C R U I T I N G A N D R E TA I N I N G
V I TA L G E N E R AT I O N Z TA L E N T

PERSPECTIVES FROM THE WORKPL ACE
The oldest members of Gen Z have already entered the workforce,
accumulating four to five years of experience and providing valuable
insights into their impact on business. Simultaneously, the demand
for their digital native skills has exponentially increased, underscoring
the importance of comprehending and meeting their uniquerequirements. While differences persist between individuals, Gen Z
characteristics can be generally distilled into four main areas:

1. HIGH KNOWLEDGE COUPLED WITH
A HIGH DEMAND FOR PURPOSE
Thanks to the internet, a majority of Gen Zers (52% in our research)
possess preconceived notions about the world of work, formingstrong opinions about specific companies and industries basedon observed actions — mostly through the internet. They exhibit
higher expectations than previous generations and, akin to Gen Y,
seek employment with organizations that align with their values andpurpose. Notably, financial motivation ranks higher for Gen Z, with
30% prioritizing fair wages.

2. DISLIKE OF CONFLICT AND
A P R E F E R E N C E T O AVO I DC O N F R O N TAT I O N
Raised in the online realm, Gen Zers may question existing norms
and prove less adept in face-to-face situations. For instance, they
may challenge set working hours, preferring flexibility to completetasks efficiently. However, this lack of adherence to traditional
norms may be perceived

G EN Z PL AC ES A PREMIUM O N
AC HIE VIN G A SATIS FAC TO RYWO RK /LIFE BAL AN C E , WITH
57 % O F TH O S E IN O UR SURVE YC O NS IDERIN G IT C ENTR AL TO
A SUC C ES S FUL CAREER .

as unprofessional by older
generations. Additionally,
their digital upbringing may
result in a lack of teamwork
experience, which would
make them more comfortableworking independently.
Conflict avoidance is

a notable trait, and if they feel undervalued or unheard, Gen Z
individuals are inclined to leave rather than engage in disputes, which
underscores the pivotal role of managers in their retention.

3. FOCUS ON WORK /LIFE BAL ANCE
AND JOB FLEXIBILIT YGen Z places a premium on achieving a satisfactory work/life balance,with 57% of those in our survey considering it central to a successfulcareer. Motivated by the desire to safeguard their mental and physicalwellbeing, they seek employer support, including access to wellbeing
services, as standard. Notably, they exhibit a propensity to switch
jobs regularly, especially if they feel unchallenged or underdeveloped.

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ARTHUR D. LITTLE

Retaining them beyond the initial learning and productivity phase iscritical for organizations to realize the returnon investment from their recruitment.

4 . DYNAMIC WORK E THIC WITH
CROSS-FUNCTIONAL ENGAGEMENT
Although Gen Z may challenge the need for set working hours, theirwork ethic remains strong when they are engaged properly, whichleads them to exceed expectations — contrary to what somemight believe.
“In fact, Gen Z’s level of engagement is high when they feel connected
to a task. Sometimes, when they are too excited, they tend to go
overboard, and actually even put in 150% of their personal attention
and effort. Yet, when they are not excited, it’s difficult to engage them.”

Hareth Alsahan, CHRO, Tawal
Given their wider interests and multidimensional digital skillsets,
Gen Z often does not feel confined by the boundaries of a specificfunction, instead expecting to work across departments and areas.
This creates challenges for traditional organizational structures put
in place to deliver clear responsibilities and accountability.
Figure 2 shows that Gen Z has strong requirements across several
areas. When asked to choose the three most important aspects of a
successful career, nearly two-thirds of participants listed earning ahigh salary as one of the factors. They also aspire to achieve work/
life balance while seeking managerial roles and constantly developing
new skills.

65%
57%
EARNING A HIGH SALARY
ACHIEVING WORK-LIFE BALANCEATTAINING LEADERSHIP OR MANAGEMENT ROLES

52%

48%

43%
35%

CONSTANTLY LEARNING AND DEVELOPING NEW SKILLSREACHING A HIGH LEVEL OF JOB SATISFACTION
MAKING A POSITIVE SOCIAL IMPACT

FIGURE 2: SUCCESSFUL CAREER FACTORS OF GENERATION Z

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P R I S M : T H E F U T U R E W O R K F O R C E — R E C R U I T I N G A N D R E TA I N I N G
V I TA L G E N E R AT I O N Z TA L E N T

UNLO C K IN G G EN Z ’ S IMPAC T
Businesses are grappling with global scarcity of digital skills — evenmore so today with the advent of AI. This lack of digital tech talentposes an existential threat to business growth and innovation, withnearly 60% of employers reporting that not having enough skilledemployees has a major or

G EN Z C O NTRIBUTESS PEED AND C RE ATIVIT Y
TO O RGANIZ ATI O NS ,C O MPLEMENTIN G E X IS TIN G
S TREN GTHS IN PRO C ES S
AND PERFO RMAN C E .

moderate impact on theiroperations. HR expert and coauthor of this article Jérémy
Lamri terms this challenge
the “Talent Bomb,” which
signals the looming threatof a skills gap jeopardizingorganizational success. Gen Z
emerges as a crucial force indefusing this bomb, offering essential digitalization and innovation
skills. Notably, 74% of Gen Z individuals in our survey express positivity
toward technology and AI, with none strongly opposing their rapid
adoption.
Gen Z contributes speed and creativity to organizations,complementing existing strengths in process and performance. Their
key skills and attitudes span:– Technology proficiency: As digital natives, Gen Z is positioned toassist companies in navigating dynamic technology and AI-driven
markets.
– C ommitment to learning: Gen Zers, raised with easy access toonline courses, YouTube, blogs, Wikipedia, and now generative AI,
actively develop their skills, propelling organizational advancement
through continuous learning.
– Entrepreneurial mindset: Embracing failure and avoiding blind
loyalty to methods, Gen Z exhibits openness to cultural change anda boundaryless approach to functions and teams.
– Inclusive thinking: Advocating for empowerment and meritocracy,
Gen Z prioritizes skills over gender or color, challenging traditional
hierarchies.
– Focus on purpose: Aligning with broader trends, Gen Z seeks
organizations that have a clear sense of purpose, integrating values
such as sustainability and ethical practices alongside financial
performance.

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ARTHUR D. LITTLE

TA I L O R I N G T H E W O R K P L A C E F O R
G E N Z : S T R AT E G I C R E C O M M E N D AT I O N S
FOR EMPLOYERS
Building a Gen Z-compatible organization, while meeting the needs ofother generations and creating ambidextrous structures, requires indepth change management, focusing on five areas:

1 . E S TA B L I S H I N G A V A L I D S E N S E
OF PURPOSEGen Zers are looking to work for organizations that share their senseof purpose, and already have strong opinions about many companies
and industries based on their expansive networks and extensive
internet exposure. Companies therefore need to transform andembrace this sense of purpose in everything they do, aligning it with
their values to change their organizational DNA and working culture.
When asked to describe their ideal work culture, Gen Z responses
included:– “An environment in which I am able to continue to learn and develop
my skills, while also being able to maintain a healthy lifestyleoutside of work.”– “A place where everyone is supportive, and I wake up excited to
go to work.”– “ Hybrid, challenging, aligned to my job aspirations, nocorporate politics.”
Based on the earlier work of psychologist Kurt Lewin, transformations
generally fit into one of two models:	1. Type I transformation: Adopting certain values (such assustainability), but not embedding them within the organization’s
economic model. Companies adopting this transformation assume
their responsibilities (such as to the environment) without radicallymodifying their activities to align with that responsibility. In
other words, the dominant nature of economic performance is
not questioned, but rather, reconfigured to integrate ecologicalchallenges. The primary business motive remains profit, but withthe aim of “doing less harm.”	
2 . Type II transformation: Undergoing deep structural changes
when adopting a value (such as sustainability) and integrating
it at every level of the organization’s operations. This type oftransformation requires emotional intelligence, open-mindedness,
and a holistic vision. Type II transformation is a mutation, aprofound change that requires courageous questioning of thestatus quo, intense awareness, and a strategic vision.

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P R I S M : T H E F U T U R E W O R K F O R C E — R E C R U I T I N G A N D R E TA I N I N G
V I TA L G E N E R AT I O N Z TA L E N T

While Type I transformations may be a first step toward adopting
important ecological values, they won’t meet the expectations of Gen
Zers who look for an employer that “walks the talk.” Gen Zers may view
it as window dressing, which can be counterproductive to attraction
and retention efforts.

2 . CHANGING MANAGEMENT AND
L E A D E R S H I P B E H AV I O R SManagers, particularly from older generations, must adapt behaviors
to accommodate Gen Z’s aversion to criticism, strong opinions, anddesire for independence. This requires patience and open-mindedness
to new perspectives from managers. Transformative leadership styles,
emphasizing empathy and encouraging creativity, resonate well withGen Z. For example, rather than a simple presentation at their annual
performance review, a Gen Z employee may go further and propose
creating a video displaying their achievements. Managers need to give
Gen Z the space to experiment in these ways.
Gen Zers highlighted some of the challenges they face within theworkplace, citing, for example:– “ Not being taken seriously, with a negative outlook on ourcapabilities, being underestimated.”– “ Unspoken rules that are outdated.”– “Gaining trust/respect from older employees is not easy,
especially in leadership positions.”

3 . C R E AT I N G A TA I L O R E D E M P L O Y E E
JOURNEY
The sense of purpose and concern for Gen Z values has to extend
across the employee journey from initial talent attraction and thehiring process, to developing their skills, all the way to their departureand staying in touch. Essentially, the double helix of organizational
DNA (purpose and identity) has to be present at every step of theemployee journey (see Figure 3).
Purpose and identity must permeate every step of the employee
journey, which necessitates an organization-wide commitment.
Employee journey thinking benefits the organization by creating
specific personas and tailored touchpoints for each cohort, which
can be used to deliver value, as well as attract and retain Gen Z
employees.

42

ARTHUR D. LITTLEORGANIZATIONAL DNA

EMPLOYEE JOURNEY

WHAT GUIDES US?

WHAT VALUE DO WE
OFFER OUR EMPLOYEES?

ATTRACTPURPOSE/MISSION &VISIONHIRE
ONBOARDPERFORM
DEVELOP
DEPART
STAY IN CONTACTIDENTITY

FIGURE 3: ORGANIZATIONAL DNA (PURPOSE AND IDENTITY) IN RELATION TO
THE EMPLOYEE JOURNEY

4. TRANSFORMING STRUCTURES AND
W AY S O F W O R K I N G
Flexible, creative organizations require agile ways of working that
replace bureaucracy and hierarchy with a lateral, competencebased approach. Gen Z employees thrive in this environment andculture, which brings creativity to

FLE X IBLE , C RE ATIVEO RGANIZ ATIO NS REQ UIREAG ILE WAYS O F WO RK IN G
THAT REPL AC E BURE AUC R ACY
AND HIER ARC HY WITH A
L ATER AL , C O MPE TEN C EBAS ED APPROAC H .

existing structures and creates
ambidextrous organizations. Thistransformation benefits overallbusiness performance, creating aholacracy 1 that focuses on skills,
capabilities, and ideas, rather
than seniority.

1. Holacracy is a system of self-management in which leadership roles
are not subject to a traditional hierarchy of command.

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P R I S M : T H E F U T U R E W O R K F O R C E — R E C R U I T I N G A N D R E TA I N I N G
V I TA L G E N E R AT I O N Z TA L E N T

Omantel — Embracing Gen Z
Telecom company Omantel has transformed how it operates tobenefit from Gen Z skills. It has built a pipeline of talent to selectpotential candidates from schools, and partners with leading
universities to develop their skills through undergraduate courses.
Once they enter the firm, they are positioned as experts from the
beginning, with promotions and opportunities based on ideas andresults, rather than length of tenure. Examples include:– Its leadership program, which allows Gen Z employees to shadow
the executive team, both on a day-to-day basis and through ashadow board. They tackle and discuss the same agenda as themain board, providing their own insights and ideas, thus enriching
the decision making process.
– Its “No Boundaries” program enables employees to explore
initiatives in any functional area, regardless of their role, breaking
down barriers and providing new perspectives.
– Its in-house innovation program, “fikra,” enables employees
to submit ideas and develop them via sabbaticals into viablebusinesses. Successes include OMPay, a payment service provider,and Sayyad, an app to link fishermen to markets.

“It is very hard to retain Gen Z and its skills, requiring transformation in
how we operate. The days of top-down decision making are long gone,
meaning we’ve put in place the programs to get the best from Gen Z totransform the organization.” Chief People Officer, telecoms provider

5 . E MP OWE RIN G E MPLOY E E S
WITH SUPPORT AND TOOLSGen Z employees are eager to develop and fast learners. Over threequarters (78%) say a company’s commitment to providing ongoingcareer development opportunities influences their job choices.
Therefore, providing them with the opportunities to grow is essential
for their retention. This could be done within their current role,or, given their desire for change, through other roles within theorganization, such as via rotation programs.

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ARTHUR D. LITTLE

As digital natives, Gen Zers expect to have access to relevant
technology within their roles. Empowering them with the righttechnology and tools (such as AI) will enable them to use their digitalknowledge to lead and drive wider digital transformation within theorganization. Not only will this benefit the business overall, but it
will also enable employees to act as ambassadors for technology
adoption, working with older generations to explain its benefits andmotivate others to adopt it.
By 2035, Gen Z will be the largest generation in the workforce, taking
up more management roles, reshaping the workplace, and refocusingorganizations. Successful companies will focus on life-long learning,
openness, and transformative leadership. This will enable themto meet the changing needs of markets that are also increasingly
dominated by Gen Z consumers. Recognizing and aligning withthe motivations and preferences of Gen Z is crucial for shaping HR
strategies, underlining the significance of a nuanced approach thatavoids broad generalizations and respects the distinct individualityof each employee. Furthermore, establishing an agile and lateralorganizational structure that allows Gen Z to thrive within a diverse,
multigenerational workforce is pivotal for positioning organizations
favorably in the ever-evolving future.

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P R I S M : T H E F U T U R E W O R K F O R C E — R E C R U I T I N G A N D R E TA I N I N G
V I TA L G E N E R AT I O N Z TA L E N T

INSIGHTS FOR THE EXECUTIVEAs organizations set sail into the Gen Z-driven future, HR
professionals and CEOs must chart a strategic course to attract andretain this unique talent pool. Here are some first steps to integrate
Gen Z into the workforce:
1. Cultivate open dialogue, collaboration, and understanding:Establish channels for transparent communication between
leadership and Gen Z employees, while encouraging crossgeneration dialogue to actively address challenges andopportunities.
2. R eassess current employee journey approaches: Examine
current practices in recruitment, engagement, and retention toalign with the unique needs of Gen Z. Consider adjustments inareas such as compensation, evaluation metrics, and working
hours to attract and retain Gen Z talent. In doing this, companies
should adopt a personalized approach, meeting individuals on
their terms, and offer a diverse “portfolio of rewards” that allows
employees to select options aligned with their preferences andmotivations, rather than adopting a one-size-fits-all strategy.
3. Implement initiatives with Gen Z needs in mind: Co-develop
strategic company initiatives around diversity, equity, andinclusion (DEI), as well as professional development, alongside
Gen Z employees, ensuring alignment with their needs.
4. Establish continuous feedback and adaptation mechanisms:
Implement robust systems for receiving feedback fromGen Z employees and the broader workforce regarding theeffectiveness of initiatives, and adapt strategies accordingly.

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ARTHUR D. LITTLE

LOKESH DADHICH
is a Partner in Arthur D. Little’s Dubai office and amember of the Telecommunications, Information
Technology, Media & Electronics (TIME) andPerformance practices.
MARTEN ZIERIS
is a Partner in Arthur D. Little’s Frankfurt office and amember of the Transformation practice.
SARA NASAIF
is a Business Analyst in Arthur D. Little’s Manama office
and a member of the Transformation practice.
HENRI LEHMANN
is a Business Analyst in Arthur D. Little’s Frankfurt
office and a member of the Performance practice.
JÉRÉMY LAMRI
is an HR expert and author.

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P R I S M : WHY PATIENT CENTRICITY IS KEY TO LONG-TERM
PHARMA COMPANY SUCCESS

WHY
PATIENTCENTRICITY

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ARTHUR D. LITTLE

IS KEY TO LONG-TERM
PHARMA COMPANY
SUCCESS49

P R I S M : WHY PATIENT CENTRICITY IS KEY TO LONG-TERM
PHARMA COMPANY SUCCESSAUTHORSBen van der Schaaf, Ben Enejo, Emmanuel Aisabokhae,
Shreya Modi, Vivien Fergusson

Patient centricity seems to be an obvious
focus for pharmaceutical companies.

After all, their core business is to develop
drugs and treatments to meet specificpatient needs.

Yet, patient centricity is not evident
across the end-to-end pharma value

chain, from identifying unmet patientneeds through drug discovery anddevelopment to product availability andtreatment. For example, on average, 30%of patients leave clinical trials before

their scheduled treatment completiondate, often because of the high burden of
the trials on their lives.

Poor patient centricity has a direct impact on company success — notlistening to the “Voice of the Patient” or failure to communicate withthem effectively can cause delays in clinical trial completion. This
may then lead to loss of commercial opportunities due to delayed
regulatory approval. On the post-approval side, misalignment withpatient needs may lead to poor uptake of the medicines and missed
financial targets.
True patient centricity is therefore increasingly becoming a key
determinant of success for pharmaceutical businesses. Advances intechnology such as AI support this, for example, enabling companies
to find patients much more efficiently. The real winners will becompanies that are prepared to see patients as the cornerstonearound whom the entire process is built, from drug discovery tocommercialization, and invest the right amounts of money, time, andresources to understand patient needs. In this environment, only
companies that truly understand what drives their target patient
population and adjust their practices to become more patient centric
will stand any chance of success.

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ARTHUR D. LITTLE

With focus on the end-to-end value chain, this article explains how
pharma companies can become truly patient centric. Many of theinsights can also be applied more broadly across other industries
where customer centricity is increasingly critical to success.

T H E G R O W I N G N E E D T O P U T T H E PAT I E N T
AT T H E C E N T E R O F D R U G D E V E L O P M E N T
As in other industries, pharmaceutical companies must become
more customer centric and compete by providing the products thatpatients require, when and where they need them. This is increasingly
important because patients are becoming more informed and expect
treatments to meet their needs. In addition, patient advocacy groups
are more active and vocal about considering patients’ needs in the
drug development and commercialization process. Patient centricity
therefore must be a key factor at

AS IN OTHER INDUS TRIES ,PHARMAC EUTICAL C O MPANIESMUS T BEC O ME M O RE
CUS TO MER C ENTRIC AND
C O MPE TE BY PROVIDIN G THE
PRO DUC T S THAT PATIENT S
REQ UIRE , WHEN AND WHERE
THE Y NEED THEM .

every stage of the pharmaceuticalvalue chain to maximize thesignificant investment (see Figure1) required for success with aninnovative drug.
Clearly, designing and launchinga blockbuster drug won’t deliver
benefits if supply chain issues
mean it is unavailable to potential

customers. A current, very clear example of this is Wegovy from Novo
Nordisk. Initially intended for diabetes patients, this drug has beenfound to help weight loss, which has dramatically accelerated its
demand. Although the company is working hard to expand capacity,
access to Wegovy is now restricted in a number of countries, to thepoint of restrictions on exports and prescriptions for non-diabetics.

STAGES

1

2

3

DISCOVERY AND EARLY
DEVELOPMENTDISCOVERY AND LATE DEVELOPMENTCOMMERCIALIZATIONDRUG DISCOVERY

TIME

PRE-CLINICALRESEARCH

PHASE 1PHASE 2

PHASE 3TYPICALLYTENSTYPICALLYLOWER
HUNDREDSTYPICALLYHIGHER
HUNDREDS

3–6 YEARS

6–8 YEARSAPPROVALMANUFACTURING

MARKETING

INDEFINITE

FIGURE 1: THE PHARMACEUTICAL VALUE CHAIN

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P R I S M : WHY PATIENT CENTRICITY IS KEY TO LONG-TERM
PHARMA COMPANY SUCCESS

We focus on three key areas of the value chain where patient
centricity should be central — understanding unmet needs in
discovery and early development, clinical trials in late development,
and the post-approval/commercialization phase.

What is Patient Centricity?
While some companies describe their approach as patient centric,
few put the patient at the heart of how they design and deliver theiractivities. We define patient centricity as: putting the patient firstin an open, sustained engagement of the patient to respectfully andcompassionately achieve the best experience and outcome for that
person and their family.

U N D E R S TA N D I N G U N M E T N E E D S I N
D I S C O V E R Y ( E A R LY D E V E L O P M E N T P H A S E )The drug development process first focuses on patients whencompanies identify an unmet need or one that can be met more
successfully through new approaches in order to create a target
product profile (TPP). While this may appear simple, multiple factors
are involved. For example, the need must be commercially viable,
whether in terms of the size of the patient population or access tofunding for drugs. This calculation has meant developing drugs forcommon diseases or new antibiotics in poorer, developing countries
has been curtailed by lack of a commercial market. However, newapproaches, such as funding from governments, charities, and NGOs,
potentially change this equation, as shown by the recent introductionof GSK’s RTS,S vaccine against malaria, which is funded by Gavi
(whose members include pharmaceutical companies); the Vaccine
Alliance; the Global Fund to Fight AIDS, Tuberculosis and Malaria;
and Unitaid.

PAT I E N T C E N T R I C I T Y I N C L I N I C A L T R I A L S( L AT E D E V E L O P M E N T P H A S E )Clinical trials take up a significant share of effort and resources
invested in the drug development process. The main factor that
distinguishes them from other stages is the direct involvement ofconsenting humans as subjects. Clinical trials have evolved over time
— early drugs were tested with a lot less regulation than is presently
in place. In some cases, drugs were tested on prisoners or otherpeople without consent. Events such as the thalidomide scandal led
to regulatory changes, which have contributed significantly to theevolution of clinical trials.

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The Clinical Trial Process and Informed Consent
One of the first clinical trials took place in 1796, when English
physician Edward Jenner tested his theory that exposure to cowpox
could prevent patients from developing smallpox. Using some cowpox
material, he inoculated his gardener’s nine-year-old son. His theory
was validated, as the “subject” gained protection against smallpox.
The process for testing treatment ideas and technology has
become much more sophisticated over the years. A clear regulatory
requirement states that patients in a trial must provide their informed
consent, which demonstrates the need for patient centricity. Unlike
in Jenner’s case, this means providing participants with adequate
information, making it as simple, direct, and honest as possible toensure it is understood, as well as giving the participants sufficient
time to ask questions and think it all through. As in other industries,
this is essential customer communication, but in many cases in thepharmaceutical industry, it is overcomplicated and not standardized.

Recruiting and enrolling patients in trials has always been a challenge
for the pharmaceutical industry. However, it is becoming moredifficult for a number of reasons, which is driving a need for greater
patient centricity to encourage increased patient involvement:– For many conditions, approved, effective drugs are alreadyavailable, which lowers the incentive for patients to take part in a
new trial with unknown benefits. The number of new trials is also
increasing overall, as shown in Figure 2.

CLINICAL TRIALS REGISTERED ON CT.GOV PER YEAR (IN 000s)
4036.7 37.0

35
30

27.8
23.3

25
20

17.6 17.0 17.3 17.8

15

12.8

10.9

29.2

30.9

38.0

37.0

32.5

24.1

19.5 20.4

12.5

10
5

2.1

1.8

1.4

3.6 3.2

0

FIGURE 2: INCREASES IN CLINICAL TRIALS SINCE 2000

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P R I S M : WHY PATIENT CENTRICITY IS KEY TO LONG-TERM
PHARMA COMPANY SUCCESS– An increasing number of trials are for drugs targeting rarer
diseases, with consequently smaller available patient populations.
– Relevant patients may have particular challenges with taking partin trials because of their location and personal circumstances.
For example, if a drug targets a condition prevalent in patients intheir 70s with mobility and technology challenges, it needs to use
non-digital channels to communicate and ensure that trial sites areeasily accessible.
– Patients may have difficulty finding the right trial for their specificcondition, for example, if they suffer from a particular rare typeof cancer. However, specialist organizations now exist to match
patients to trials. Finding patients for trials and trials for patientshas become its own industry, driven by large amounts of data (suchas through X [formerly known as Twitter], Facebook, and specialist
electronic health record [EHR] companies, with many startups
developing their own algorithms to match patients and trials).
Clinical trial retention is also an issue, particularly as patients, like all
customers, now have higher expectations for how they will be treated.
Patients may drop out of clinical trials for several reasons, such as:– They don’t see an impact from the trial, particularly if givena placebo.
– They suffer from minor and/or major side effects.
– They move far away from the trial site (which is particularly an issue
for centralized trials).
– They are unable to continue a commitment to longer-term trials
because of changing circumstances, such as those where they aretested weekly for many months.
Making trials attractive to patients requires focus on three key areas:

1. TRIAL DESIGN
Trials need to be built on an understanding of the needs of thepatient, rather than solely the requirements of the regulator and trial
sponsor. These needs must be considered holistically — not just thepatient’s medical condition and how it impacts their life, but also theimpact of the trial on their jobs, their family situation, and theircare providers.

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ARTHUR D. LITTLE

2 . P AT I E N T B U R D E NGiven the choice, patients will naturally choose trials in which
they have to do as little as possible and will gain as much as
possible. Applying this understanding to trial design is therefore
vital: minimizing the patient burden and eliminating barriers toparticipation, such as shortening their length, organizing home visits,
or arranging transport to trial sites.

3 . P AT I E N T B E N E F I T
Patients join trials with the hope that it will improve their conditionor treat their disease. Many are therefore disappointed, and may dropout, if they see no impact. Consequently, a growing number of trials
are changing the ratio of active drugs to placebos from the traditional
50/50 to 66/33, as this increases the chances of patients seeing an
improvement.

PAT I E N T C E N T R I C I T Y A F T E R A P P R O VA L
( C O M M E R C I A L I Z AT I O N P H A S E )Once a drug is moving toward regulatory approval, pharma companies
need to ensure that insurers and public health systems are willingto pay for it, particularly with highly priced drugs. This requires
engagement with key opinion leaders (generally leading doctors or
academics, or both), insurers, government bodies (such as NICE in theUK), and pharmacy benefit managers to demonstrate the advantages
against those of any existing alternatives.
As well as focusing on reimbursement, pharma companies mustensure a sufficient supply to scale to meet market needs — such as
by licensing production to third parties, as shown by the rollout of
COVID-19 vaccines. Creating

O N C E A DRUG IS M OVIN GTOWARD REG UL ATO RY
APPROVAL , PHARMAC O MPANIES NEED TO ENSURE
THAT INSURERS AND PUBLICHE ALTH SYS TEMS ARE WILLIN GTO PAY FO R IT, PAR TICUL ARLY
WITH HIG HLY PRIC ED DRUG S .

demand and then not fulfilling
it quickly enough will impact
patient relationships and leadthem to switch to alternatives,
even if technically inferior,or even purchase counterfeit
versions of popular drugs via theinternet, creating risks to theirhealth, as well as the company’s
reputation and revenues. As the
Wegovy weight loss example

demonstrates, doctors can prescribe drugs for conditions beyond
their original target, potentially making planning of production
volumes difficult. While the need for sales does mean companies haveincreased focus on patient centricity, they must also understandthat patient expectations are changing and continually improvecommercial operations accordingly.

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P R I S M : WHY PATIENT CENTRICITY IS KEY TO LONG-TERM
PHARMA COMPANY SUCCESS

From the patient viewpoint, the ease with which the treatment canbe taken is also important. For example, pills, which can be selfadministered, are simpler to deal with than infusions or treatments,
which require visits to hospitals or clinics. Improving the drug, suchas by changing its form or how it needs to be taken, makes treatment
easier for patients — while also extending patent lifecycles and thusincreasing revenues.
Any ongoing monitoring needs to be straightforward, rather thanrelying on complex medical devices or lengthy repeat appointments.
Pharma companies have learned from other industries — for example,
Novartis’ first CAR-T cancer treatment was logistically complex, highcost (around US $500,000 per treatment), and a process taking weeks.
To help patient adoption, Novartis adapted techniques from service
industries, providing a “white glove” service to patients to walk themthrough the entire process.

LISTENING TO THE VOICE OF THE
P A T I E N T — D I R E C T LY A N D I N D I R E C T LY
Pharmaceutical companies need to focus on becoming patient centricacross everything they do. They should consider how they talk about
patients internally and how they engage and communicate withthem. In many cases, pharma

ANY O NG OINGM O NITO RIN G NEEDS TO
BE S TR AIG HTFO RWARD,
R ATHER THAN RELYIN G O N
C O MPLE X MED ICAL DE VIC ES
O R LEN GTHY REPE ATAPP O INTMENT S .

companies now hold open dayson their campuses, bringing
patients on site. This not only
educates patients themselves
on development activities,
but more importantly, gives
staff direct, real world
experience of patients withspecific conditions. This aims
to embed patient centricity

in the working lives and behaviors of staff by connecting them topatients and their needs.
Technology is also a significant tool here, which can be used to learn
what patients or their carers are saying or thinking, or to directlyinteract with them through apps that support the therapy,
for example.
In the case of rare diseases, which have smaller patient populations,companies can engage directly with known individuals and nurture
relationships. However, in areas where multiple drugs are being
developed, competition for patient time can be fierce — only thosecompanies that deliver on their expectations and needs will build
viable, long-term relationships.

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ARTHUR D. LITTLE

As well as direct connections with patients, pharma companies
need to work closely with patient advocacy groups — organizations
created to represent and support patients and their families livingwith a specific condition. Often, but not always, focused on rarediseases, these groups provide a focal point for interactions withpatient communities, as well as a source of potential clinical trial
participants. They also may offer support for regulatory approval as
regulators increasingly look to patients for their views. Consequently,
pharma companies often support, fund, or sponsor patient advocacy
groups and their events and initiatives.

P R A C T I C A L W AY S T O B E C O M E M O R E
PAT I E N T C E N T R I C
Radical change is needed to improve the experience of patients
across the value chain. Of course, patient centricity can also increase
complexity and cost. However, new approaches, often driven bytechnology, can help make this easier to manage, as well as maximize
the resulting benefits. To successfully put the patient at the heartof the drug development and commercialization value chain, pharmacompanies need to focus on four key areas — putting patients first,
incentivizing participation, leveraging technology, and improving
communication/care.

1 . P U T T H E P AT I E N T F I R S T
Patients should sit at the center of pharma company thinking,from identifying needs through clinical trial design and delivery
to commercialization. The burden on patients should be kept to aminimum, and communication should be tailored and personalized
to meet their needs. Data is at the heart of delivering a scalable,
patient-first approach. Building online and offline communities, either
directly or via patient advocacy groups, nurtures strong relationships
and enables pharma companies to communicate and engage patients
globally and at scale.
As part of this, companies should look to collect as much data as
possible during trials, while remaining patient centric. This should
help minimize the need to carry out multiple trials. For example,
patient follow-up data can be used more productively by contributing
it to a central repository, where a large, anonymized data set is held
to build a better picture of a disease across drug companies andhealthcare systems.

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P R I S M : WHY PATIENT CENTRICITY IS KEY TO LONG-TERM
PHARMA COMPANY SUCCESS

2 . I N C E N T I V I Z E P A R T I C I P AT I O N A N D
MAKE PRESCRIBING AND PURCHASING
EASIER
Patients are not paid to engage with pharmaceutical companies
or take part in trials, although clearly they stand to benefit from
improved treatments down the line. Yet they provide a criticalcomponent of developing an approved drug — without the pharmacompany identifying their needs and running successful trials, eventhe most promising drug will not reach the market.
Consequently, while pharma companies covering trial-related
expenses for patients has been common practice for many years,
they can potentially go further, such as by issuing a trial completion
bonus to acknowledge and reward patient commitment. In addition,sponsors can share the proceeds of success with patients if the drug
achieves successful regulatory approval. This risk-reward sharing
approach will encourage retention of patients and demonstrate apositive patient-centric shift for pharmaceutical companies.
To increase access to drugs, companies are aiming to make buying
and prescribing simpler. For example, in the US, new legislation aims
to make access to insulin much more affordable for diabetes patients,
while pharma companies reimburse commercial patients for out-ofpocket costs (copay). This process involves many more players in thehealthcare system than just the pharma company and patients.

3 . LE VER AGE TECHNOLOGY
Harnessing technology assists in engaging with patients and lowering
their burden, both when trials begin and when drugs are prescribed.
For example, by analyzing healthcare data, AI-driven knowledge
graphs can identify patients with specific diseases or conditions,even to the level of carrying out predictive analysis to identify thoseat risk of developing a condition before it has been diagnosed. Suchtechnology-enabled approaches provide significant benefits for moststakeholders involved, from the patient to the clinical trial sponsor,
and even the overall healthcare system. As well as identifying
potential trial participants, they help find patients once treatments
are approved, particularly those suffering from rare conditions.
During and even after trials, wearable technology, such as Fitbits
and Apple Watches, as well as smaller, less intrusive sensors, cantransform monitoring by continually measuring relevant trial end
points (see Figure 3). Smart glasses and internal and external
biosensors can deliver real-time results via smartphones, lowering
the patient burden and need for physical visits to trial sites, while
increasing the speed and volume of data available. While many clinical
trials are now adopting these mobile technologies, they can still beperceived as “nice to have” or limited to a few therapy areas. In the
future, these will become the normal standards across all types ofclinical trials.

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ARTHUR D. LITTLE

INTERNAL COGNITIVE

SMART GLASSES AND EARBUDSINSTANTLY RECALL A MEMORYEXTERNAL COGNITIVEPGESTURE SENSORSREMOTE SUMMON A CAR TO THE
CURB BY SIMPLY POINTING A FINGER

INTERNAL PHYSICALBIOSENSORSCONTINUALLY MONITOR AND
ANALYZE VITAL SIGNSEXTERNAL PHYSICALAUGMENTED LEGGINGEXERCISE NORMALLY DESPITE
INJURIES OR AGING

FIGURE 3: EXAMPLES OF HUMAN AUGMENTATION

When drugs are prescribed, sensors and wearable technology canmonitor for any potential side effects (such as raised blood pressure)or indicators that show a need for further treatment. Companies canenhance adherence to treatment plans by providing apps with theirdrug to ensure that doses are taken correctly, monitor effectiveness,
and allow patients to share their experiences.

4 . F O C U S O N C O M M U N I C AT I O N
AND CARE
Pharma companies need to strengthen communication and care forpatients, but are traditionally at arm’s length from patients, withmany countries prohibiting direct sponsor contact with patients.
That means they need to educate, communicate, and train those
involved in a patient’s treatment, such as doctors, nurses, and othercare givers. This requires creating compelling, effective personalized
programs that use a mix of digital and physical channels to explain
the benefits of a drug and how it should be prescribed so healthcare
professionals can effectively convey the message to patients.

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P R I S M : WHY PATIENT CENTRICITY IS KEY TO LONG-TERM
PHARMA COMPANY SUCCESSINSIGHTS FOR THE EXECUTIVE
While the pharmaceutical industry is unique in many ways, the need
to focus on the customer/patient and design and deliver a tailored,
end-to-end service is applicable to businesses well beyond thesector. Patients, like customers, have the power of choice, which isincreasingly driving their actions, especially in competitive markets
where multiple pharma companies are developing or offering relevant
treatments.
To succeed in an increasingly customer-centric world, companies
should focus on:
1. Understand the complete impact of using or buying a productor service: How do needs change across the lifecycle, and how

can they be delivered holistically? How do you minimize customer/
patient effort and maximize their benefit?
2. L
 isten to patients/customers and trusted third parties, such as
patient advocacy groups, charities, and consumer organizations.
Involve them early in the design and co-creation of processes toensure customer centricity.
3. Build a culture focused on the patient/customer: This includes
the language used to describe customers, the minimum standards
they should expect, and commitment to putting their needs first.
4. Continually collect feedback and use this to drive improvements inprocesses and operations.
5. Embrace new technology, such as AI and wearables, to improve theexperience for patients and customers and remove bottlenecks andburdens for them.
6. Incentivize loyalty, for example, through providing bonuses forclinical trial participants or identifying and rewarding
key customers.
Focusing on the customer is a priority for every industry. Patient
centricity best practices therefore have a broader application acrossdifferent sectors, helping increase engagement, loyalty, and revenues.

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ARTHUR D. LITTLE

BEN VAN DER SCHAAF
is a Partner in Arthur D. Little’s New York office and amember of the Healthcare & Life Sciences practice.
BEN ENEJO
is a Partner in Arthur D. Little’s Boston office and amember of the Healthcare & Life Sciences practice.
EMMANUEL AISABOKHAE
is a Manager in Arthur D. Little’s New York office and amember of the Healthcare & Life Sciences practice.
SHREYA MODI
is a Manager in Arthur D. Little’s New York office and amember of the Healthcare & Life Sciences practice.
VIVIEN FERGUSSON
is a Consultant in Arthur D. Little’s Boston office and amember of the Healthcare & Life Sciences practice.

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T H E F U T U R E O F S O F T WA R E P R O D U C T S A N D S E R V I C E SSOFTWARE
REVOLUTION
HOW ARTIFICIAL INTELLIGENCEIS RESHAPING THE FUTURE
OF SOF T WARE PRODUC T S
AND SERVICESARTHUR D. LITTLEAUTHORS
Bela Virag, Nicholas Johnson, Dr. Michael Eiden, Dr. Michael Opitz,
Riadh Marrakchi, Julian Hartmann, Dr. Christian von Reventlow, Michael Majster

One of the front-row candidates for

disruption by artificial intelligence (AI) is

software product and service development.
AI is already leading to a paradigm shift
in aspects such as coding, architecture,
security, service management andticketing, and personalization, providing
new opportunities and risks. But the

implications go well beyond new products
and services and improved development
approaches, into how software

enterprises need to transform themselves
across the board, from strategy andorganization through to capabilities,
resources, and ways of working.

This is not just an issue for the software services industry itself.
As part of ongoing digitalization, enterprises across many sectors,
such as financial services, manufacturing, energy, and healthcare,are bringing software development in-house as it becomesincreasingly critical for maintaining competitive advantage. Most
large companies today have also become, at least to some extent,“software companies1.”
In this article we explore some key aspects of how companies should
go about making the necessary transformation of their software
products and services capabilities amid an AI revolution that has
already started.

1. “Corporatizing the Speedboat — How to Set Up an In-House Digital Accelerator,” ADL Viewpoint, 2023
https://www.adlittle.com/sites/default/files/viewpoints/ADL_Corporatizing_the_speedboat_2023.pdf

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T H E F U T U R E O F S O F T WA R E P R O D U C T S A N D S E R V I C E S

THE IMPAC T O F AI O N S O F T WARE
PRODUCTS AND SERVICES
The revolution that AI is bringing to software development has many
dimensions. We refer to these conveniently here under the acronym
CRASHED:– C - Continuous learning software: AI enables software thatevolves in real time, leveraging user feedback and continuously
generating new updates and versions. For example, AI-driven
customer service platforms can adapt their responses andstrategies based on ongoing customer interactions and feedback.
– R - Revolutionizing architectures: Given its huge dependency
on data, AI connects directly to databases, making traditional
enterprise software architectures obsolete. For example, AIenhanced database management systems can autonomously
optimize queries and storage, reducing the need for manual
database tuning.
– A - AI-driven software development: AI assumes the roles ofcoders and testers, with human oversight focusing on specificationand teaching. For example, an AI system can automatically generate
and test code for a new application feature based on high-level
design inputs.
– S - Security enhancement: With AI, new cybersecurity threats
emerge, necessitating advanced solutions such as zero-trustarchitectures and real identity verification to significantly
enhance security. One example is implementation of zero-trust
security models in corporate networks, in which AI monitors andauthenticates every device and user continuously.
– H - Hyper-personalization: AI enables highly personalized user
experiences, diminishing the relevance of generic, one-size-fitsall software solutions. For example, e-commerce platforms using
AI can provide individualized shopping experiences, with productrecommendations uniquely tailored to segments of one2 .
– E - Exponential acceleration: Development and adoption of AI
is occurring at an exponentially accelerating pace, and showing
no signs of plateauing at present. This means even more rapid
development and deployment cycles for software companies, withnew features being released and updated on a weekly or evendaily basis.
– D - Decentralized autonomous systems (DASs): Combined withedge computing, AI is driving further developments of DASs. DASs
operate independently and are capable of self-updating, selfrepairing, and autonomous evolution, leading to new developments
such as verifiable claims and smart contracts. For example, anautonomous, decentralized supply chain management system canself-adjust based on real-time data, without central oversight.

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2. Refers to treating individual customers as unique segments.

ARTHUR D. LITTLE

Although some of these new capabilities are still in development,
many use cases are already here. For example, AI tools are alreadyassisting developers and testers by automating routine tasks andoptimizing DevOps workflows. A recent benchmarking exercise
conducted by Fonds Finanz looked at the efficiency benefits of
GPT4, GPT3.5, Code Llama, Llama Chat, and StarCoder for coding andtesting. It concluded that time and cost savings of 50–60% had beenachieved in code generation and conversion for tasks involving no
significant shift in logic or functionality, as well as 30% savings fortesting and 60% for documentation. Even where logic or functionality
was changing, benefits of 10–30% were demonstrated.
Code conversion from one language to another, for example, from an
old language such as COBOL to a modern language such as Python
or Java, is another area where AI

PERHAP S THE M O S T
FUTURIS TIC AS PEC T O F AI IN
SO F T WARE DE VELO PMENT IS
THE EMERG EN C E O F S ELFDE VELO PIN G SO F T WARE .

can reduce the time needed fromweeks or months to minutes. Thisis valuable for preserving thefunctionality of legacy systems,
one of the biggest challenges facedby large corporations especially.
It is also the precursor to humans
specifying the requirements and the

AI generating the code and the tests itself, which will lead to entirely
new programming paradigms and languages.
Perhaps the most futuristic aspect of AI in software development
is the emergence of self-developing software, whereby systems
can create, optimize, and even repair themselves without humanintervention, leading to software that is perpetually up to date andoptimally efficient. A recent example is the STOP system developedby Stanford in collaboration with Microsoft research. STOP stands for
Self-Taught Optimizer, and is a method whereby a language model isapplied to code to improve arbitrary solutions recursively.

THE RI S KS FO R C O MPANIESClearly, the transformative nature of AI poses risks as well as
opportunities for companies developing software products, withcompanies that are slow to adapt losing ground rapidly to theircompetitors. Conversely, companies that move too fast with unproventechnology risk getting themselves into trouble. Many specific risks
must be dealt with, for example:

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P R I S M : S O F T WA R E R E V O L U T I O N — H O W A R T I F I C I A L I N T E L L I G E N C E I S R E S H A P I N G
T H E F U T U R E O F S O F T WA R E P R O D U C T S A N D S E R V I C E SSYSTEMS AND ARCHITECTURE– Substitution of current software system offers by new
AI-driven architectures– High costs of transitioning to new architectures– New challenges in managing decentralized software systems– C ontrolling the risks of AI-generated errors or biases being
propagated at scale

SECURITY– New cybersecurity vulnerabilities and attack surfaces requiring
new responses– New data security, privacy, and ethical issues to be managed

D ATA– High dependency on data quality from legacy systems– Need for differentiated data sources, including beyond
corporate borders

S K I L L S A N D C A PA B I L I T I E S– Upskilling of teams to adapt to new technologies and workflows– Loss of core software skills as AI takes over– Lower development barriers to entry, leading to an influx of
new competitors
Today’s large software organizations could find their existing businessmodels, platforms, and system offerings severely disrupted by theserisks, with new, more agile competitors posing a significant threat.
Companies whose core business is outsourced software services
could find their very existence threatened by AI substitution. B2B
customers of software products and services, and those customers
that have already brought software development in-house, also face asteep learning curve to integrate and adapt to new systems.

INSIGHTS FOR THE EXECUTIVE — HOW
C O MPANIES S H O ULD RES P O ND
Companies in the software industry, or that run significant in-housedigital factories or incubators in other industries, need to conduct
a thorough strategic review and establish change plans to ensurethat they continue to thrive and prosper as the AI-driven revolution
gathers pace. Many aspects must be considered, as shown in
Figure 1.

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ARTHUR D. LITTLE

1

STRATEGY &ORGANIZATION
2PROCESSES ANDSERVICE OFFERINGS
3

PARTNERSHIPS AND COLLABORATIONS4CAPABILITIES AND RESOURCES

5ETHICS AND GOVERNANCE

FIGURE 1: SHAPING UP FOR THE AI SOFTWARE INDUSTRY REVOLUTION

1 . R E V I S I T S T R AT E G Y A N D
O R G A N I Z AT I O N
A good place to start is to revisit strategic aims and objectives
to set the right direction for transformation. For large incumbent
companies whose core strengths

G IVEN THAT AI IS FUELIN GR APID AC C ELER ATI O N O F
INN OVATI O N , C O MPANIESNEED TO C O NS IDER WHE THER
THEIR E X IS TIN G INN OVATIO N
EFFO R T IS S TILL FIT FO R
PURP O S E .

are being significantly impacted
by AI, defensive tactics could be
an important part of the strategy.
In practice, this could mean
strengthening core competencies
that are not easily replicable byAI, such as exceptional customer
service, specialized market
knowledge, deep customer
relationships, and investing inproprietary technology. This is, in a sense, the “Apple strategy”:
locking in customers and fostering brand loyalty by developing aunique ecosystem of interconnected products and services, focusing
on innovation, design excellence, and a high-quality user experience.
Given that AI is fueling rapid acceleration of innovation, companies
need to consider whether their existing innovation efforts are still
fit for purpose. Creating a separate division or subsidiary dedicatedto AI innovation allows for agile exploration and development of AI
opportunities without impacting the primary business, and helps toencourage breakthroughs. Alphabet’s formation of Google AI is one
obvious example of a successful use of this approach.

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T H E F U T U R E O F S O F T WA R E P R O D U C T S A N D S E R V I C E S

In terms of organizational structures, exploiting AI effectively
requires fluid, dynamic, and collaborative models. This could include
more cross-cutting functional, matrix, and network structures toenable better multidisciplinarity and cross-unit synergies. As AI
automates routine tasks, we could expect flatter structures to be
more suitable, with enhanced unit autonomy due to better real-timedata and analytics.
Leadership roles will need greater emphasis on orchestration,
facilitation, and continuous change. AI’s predictive analytics and
DAS’s transparency could lead to more data-driven decision making
processes, reducing reliance on hierarchical decision making.

2. REFRESH PROCESSES AND DEVELOPNEW SERVICE OFFERINGS
Clearly, identification and development of new AI-driven service
offerings has to be a key aspect of transformation, requiring the usual
dual pull/push focus on deep understanding of customer and market
needs, together with new technology capabilities and opportunities.
In terms of processes, companies will need to cultivate data-centric
decision making, leveraging AI insights and equipping leaders andteams with the latest tools and training. They will need to deploy
advanced tools that support communication and collaboration,
particularly for teams working with remote and decentralized systems(even sometimes between corporations).

3 . E X T E N D PA R T N E R S H I P S A N D
C O L L A B O R AT I O N S
One key for success will be doubling up on efforts to engage instrategic partnerships with other companies, research institutions, orstartups in the AI field. Increasingly, the philosophy should be evolved
away from “This is our business, so who can we best partner with?”and toward “These are our competencies and strengths, so how can
we best combine these in new ways with those of others to create new
businesses?” This means fostering greater openness with data anddeveloping partnerships on the basis of mutual trust rather than legal
protection. For instance, depending on the use cases and expected
response time, new and converging partnerships with telcos aroundinfrastructure could come into the picture to optimize (near-) realtime interactions.

4. RESKILL AND UPSKILLC A PA B I L I T I E S A N D R E S O U R C E S
In some ways, this is the greatest challenge for companies in the AIdriven revolution. A major shift is needed from traditional softwaredevelopment to areas such as AI model training, data analysis, andethical AI design. This necessitates reevaluation and disruption ofcurrent educational and training programs, reskilling of certain
job functions (such as coding and testing), a new commitment tocontinuous learning, and fostering an adaptive culture. Investment ininnovation and R&D resources to accelerate the innovation effort isalso a key aspect.

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ARTHUR D. LITTLE

Given the direct proportionality of the “intelligence” part of AI
with the ingested data, we also expect a refocus on foundational
data-related capabilities — data governance and data scouting
to identify value-adding data sources that could lead to adifferentiated outcome.

5. RE VIEW ETHIC S AND GOVERNANCE
Relying on AI for software development raises new ethical questions,such as bias in AI algorithms and the potential misuse of AI-developed
software. Additionally, ensuring the security and reliability of AIgenerated software could pose new challenges for the industry.
New frameworks and policies will be required based on clear ethicalprinciples. These will need to ensure adequate coverage and robust
enough control of risks such as safety, security, confidentiality,and privacy.
The case example shows an example of a software and data services
company in Germany that has successfully adopted a thoroughapproach in transforming itself for an AI-based future.

Case Example — Transitioning a Software/Data Services Company
to an “AI First” Model

A company that provides standardized software to the majority of theGerman insurance industry is making the transition toward becoming
AI-based. Previously, its software was powered by data that was
manually extracted from very large numbers of documents provided
by various players in the industry, which required ever-increasing
manpower. Working with ADL, the company applied a structured
transformation approach to begin the AI transition:– New “AI first” strategy: The first step was to reshape the strategy
toward AI, a key part of which was to recognize the new business
opportunity in providing insights, namely, “insights are the new oil”
(rather than, “data is the new oil”). The organization was reshaped
around AI-based operations, training, and results verification, with
newly freed-up resources able to start a new business unit aroundprovision of insights.
– Redesign of core processes: Rather than attempting to forcefit introduction of AI into existing processes, processes werereassessed and redesigned around AI-based execution. Thisrequired new and modified process steps in which humans
interacted with AI as drivers or pilots to guide, provide sense
checks, monitor, and improve. Transitioning was done in multiple
stages, beginning with low-hanging fruit around efficiencies andmajor cost pools. “Insights-as-a-service” was introduced as anentirely new offer.

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T H E F U T U R E O F S O F T WA R E P R O D U C T S A N D S E R V I C E S– Staff upskilling: Staff members were upskilled to enable thetransition, and some new staff were hired for the transition
journey and new insights unit. Nearly every role was redesigned
for augmentation by AI copilots, with substantial employee
engagement in the changes.
– New governance and ethics council: A new council for AI wasestablished to drive thought leadership, engagement, andethical reflections and insights.
In developing the new AI-first strategy, selected customers, mainly
large insurance companies, played a pivotal role. This was especiallyvaluable in helping to identify the value pockets for the new
insights business. A technology partnership with the AI strategy andimplementation arm of a major consulting company was also key.
The efficiency gains from AI deployment allowed the company to selffund its business expansion, which resulted in double-digit growth.

IN CONCLUSION
The advent of AI and accompanying drive toward decentralized
systems is clearly a fundamental shift that is redefining not only thesoftware services industry itself, but also the way enterprises acrossall sectors go about developing software products and services. From
revolutionizing product development to reshaping organizational
structures, the impact is profound and pervasive.
As they navigate this new wave, leaders need to have clear strategic
foresight and adopt a structured transformation approach, rather
than just integrating AI tools operationally. Success will require a
blend of technological acumen, ethical considerations, and a deep
commitment to continuous learning and adaptation. The path forward
is clear: evolve, adapt, and innovate, or risk obsolescence.

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ARTHUR D. LITTLE

BELA VIRAG
is a Managing Partner in Arthur D. Little’s Vienna office and amember of the Telecommunications, Information Technology,
Media & Electronics (TIME) practice.
NICHOLAS JOHNSON
is a Partner in Arthur D. Little’s London office and a memberof the Innovation practice.
DR. MICHAEL EIDEN
is a Partner in Arthur D. Little’s London office and Global
Head of AI/ML.
DR. MICHAEL OPITZ
is a Partner in Arthur D. Little’s Munich office, Head of the
TIME practice in Central Europe, and Global Head of Segment“Time as Enabler.”
RIADH MARRAKCHIis an Associate Partner in Arthur D. Little’s Dubai office and amember of the TIME practice.
JULIAN HARTMANN
is a Principal in Arthur D. Little’s Frankfurt office and amember of the TIME practice.
DR. CHRISTIAN VON REVENTLOW
is an Associate Director in Arthur D. Little’s Vienna office anda member of the TIME practice.
MICHAEL MAJSTER
is a Partner in Arthur D. Little’s Brussels office and amember of the Innovation practice.

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BE CAREFULOUT THERE

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ARTHUR D. LITTLEUNDERSTANDING THE
RISKS OF DEPLOYINGARTIFICIAL INTELLIGENCE73

P R I S M : B E C A R E F U L O U T T H E R E — U N D E R S TA N D I N G T H E R I S K S O F D E P L OY I N GARTIFICIAL INTELLIGENCEAUTHORS
Dr. Albert Meige, Zoe Huczok, Rick Eagar

By now, business executives are wellaware that using artificial intelligence(AI), especially generative AI (GenAI)such as ChatGPT, brings with it certain
risks as well as benefits. Apart fromthe commonly cited existential risk ofa future artificial general intelligenceposing a threat to mankind, there areplenty of less severe but more likely risks.
Those that most people have read about
already are possible biases in GenAI’s
outputs, as well as its propensity to“hallucinate” on occasion.

But this is only part of the story. As adoption accelerates, it is helpful
to step back and consider the full range of risks and what needs to bedone to manage them effectively.

THE OVERALL RISK PICTURE
Risks associated with GenAI can be broadly split into two types: (1)Shortcomings of GenAI and (2) Manipulation of GenAI strengths.
Within each type are different categories (see Figure 1).

1

BIAS

HALLUCINATIONSSHALLOWNESSSHORTCOMINGSOF GEN AI

GEN AI PERPETUATESBIASES PRESENT IN
TRAINING DATA

GEN AI OCCASIONALLY RETURNSFALSE INFORMATION NOTGROUNDED IN TRAINING DATA

GEN AI FAILS IN CERTAIN NUANCED
OR SOPHISTICATED TASKS, AND
PREDICTIVE TASKS WITH A WIDERANGE OF OUTCOMES

2

MANIPULATIONOF GEN AI
STRENGTHSNEFARIOUS USAGECYBERSECURITY

GEN AI FACILITATES GENERATION OF
MISINFORMATION AND FAKES,UNDERMINING PUBLIC TRUSTGEN AI INCREASES RISKS SUCH AS
PHISHING, DATA MANIPULATION, AND
DATA PRIVACY BREACHESFIGURE 1: TWO TYPES OF GEN AI RISK

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ARTHUR D. LITTLE

SHORTCOMINGS OF GEN AI
Inherent risks arise from weaknesses in the current generation ofavailable GenAI technologies. Currently, GenAI has three major
weaknesses: bias, hallucinations, and shallowness.

B I A S : L L M S A N D G E N A I P E R P E T U AT E
OR EMPHASIZE BIASES IN TRAININGD ATAGenAI, like other algorithms based on machine learning (ML),perpetuates or emphasizes biases present in its training data. The
key concern is dominant attitudes and worldviews, including thoseof the past as well as the present, which may be over-represented
in GenAI outputs1. This can cause stereotypes to be reinforced andminority views to be underrepresented — perhaps even leading to an
artificially imposed “normalization” of thinking. These biases fall into
six main categories:
1. Temporal biases: Models may generate content that reflects
the trends, beliefs, or viewpoints prevalent during the time frame
for which the model was trained, which may not be relevant orappropriate for the current context.
2. Linguistic biases: Most internet content is in English, which meansmodels trained on internet data will perform poorly when solving
problems in other languages, particularly minority dialects.
3. Confirmation biases: Models can provide outputs that confirm
their parametric memory even when presented with contradictoryevidence. These suffer from the same confirmation biases as humans,
creating a risk that results will be polarized.
4. Demographic biases: If trained on unrepresentative data, models
can exhibit biased behavior toward genders, races, ethnicities, or
social groups, reflecting the information they learned from. For
example, when prompted to create an image of “flight attendants,”
DALL-E predominantly provides images of white women.
5. Cultural biases: Again, because of unrepresentative training data,
outputs can be biased, reinforcing or exacerbating existing cultural
prejudices and stereotyping certain groups. Figure 2 provides anexample of images generated by the prompt “American Indian.”
6. Ideological and political biases: Models can propagate specificpolitical and ideological views present in training data, as opposed
to other, more balanced views. For example, when asked to write a
program to decide who to torture, ChatGPT suggests carrying thisout systematically in North Korea, Iran, Sudan, and Syria, rather thanother countries.

1. “Will AI Take Us Into Orwell’s 1984?” ADL Blue Shift Bulletin, 2023
https://www.adlittle.com/en/insights/viewpoints/will-ai-take-us-orwell%E2%80%98s-1984

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P R I S M : B E C A R E F U L O U T T H E R E — U N D E R S TA N D I N G T H E R I S K S O F D E P L OY I N GARTIFICIAL INTELLIGENCEFIGURE 2: EXAMPLES OF DEMOGRAPHIC AND CULTURAL BIAS GENERATED BY GEN AI

Using GenAI to create fake images of underrepresented groups has
been proposed as a solution to balance data sets. However, thiscarries both functional and moral risks: who decides what needs to bebalanced, and to what extent? How would criteria be determined todecide what needed to be added?
The “EU AI Act,” provisionally agreed upon on December 8, 2023,
attempts to address the risk of bias via requirements on thetransparency and explainability of foundation models. Explainability
requires foundation model providers to account for relevant design
choices in the AI system, including the quantity and suitability ofdatasets used for training and their possible biases. Traceability andtransparency, achieved by keeping records of datasets, decisions, andprocedures, will help identify where an AI output may have gone awry,
providing faster mitigation for cases of bias.

H A L L U C I N AT I O N S : L L M S A N D G E N
A I O C C A S I O N A L LY R E T U R N F A L S E
I N F O R M AT I O N , A P R O B L E M T H AT
M AY N O T B E P O S S I B L E T O S O LV E
GenAI may provide incorrect outputs, even if the correct information
is within its training set. These hallucinations fall into two groups:
1. Knowledge-based: incorrect information
2 . Arithmetic: incorrect calculations
For example, in a November 2023 case, a team of Australianacademics had to issue an apology after using Bard, which had
generated a number of damaging and erroneous accusations
about Big Four consulting firms and their involvement with othercompanies2 . Even simple arithmetical problems can be returned witherroneous results. In all these cases, the GenAI returns errors with thesame confidence and certainty as it does with facts.

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2. https://incidentdatabase.ai/cite/614

ARTHUR D. LITTLE

The most advanced GenAI models have been observed hallucinating at
widely varying rates. The Vectara “hallucination leaderboard,”3 which
provides monitoring reports, suggests rates of 3% for GPT4 and up to
27.2% for Google PaLM2 chat. While rates are improving, this problem
will never be eradicated completely.
Hallucinations in LLMs have two causes: probabilistic inference andconflated information sources.
Probabilistic inference
LLMs calculate the probability of different words depending on thecontext, thanks to the transformer mechanism4. The probabilistic
nature of word generation in LLMs is driven by a so-called
temperature hyperparameter. As temperature rises, the model can
output other words with lower probabilities, leading to hallucinations.
Additionally, generated text aims to be more diverse, but this means it
can be inaccurate or context-inappropriate.
Conflated information sources
LLMs can sometimes conflate different sources of information,even if they contradict each other, and generate inaccurate or
misleading text. For example, when GPT-4 was asked to summarize
the 2023 Miami Formula One Grand Prix, the answer correctly covered
the initial details of the May 7, 2023 race, but subsequent details
appeared to be taken from 2022 results. For those who did notknow the right answer, the response seemed plausible, making
it a believable hallucination.
Several techniques help limit hallucinations in LLM outputs, including
supervised fine-tuning, new decoding strategies, and knowledge
graphs5. Other techniques leverage prompt engineering. Of these,
retrieval augmented generation, for example, combining LLMs withsearch engines, helps mitigate source conflation. Examples include
Perpexity.ai, which calls itself an “answer engine” and can returnthe information sources on which its response is based. The queryis provided as an input to both the model and the search engine,
and the best search engine results are then injected into the LLM,
which produces an output based on both its parametric memory
and the search engine results. Indicating information sources offers
traceability for the user, which helps build confidence in model
outputs. The ability to retrieve outside knowledge is also part ofthe capabilities built into OpenAI’s Assistants API, unveiled in
November 2023.

3. https://github.com/vectara/hallucination-leaderboard
4. A transformer is a deep-learning architecture, developed by Google Brain in 2017, that forms the basis of LLMs.
It predicts the next most likely word following a sequence. See the ADL Blue Shift Report “Generative AI – Toward
a New Civilization?” https://www.adlittle.com/en/insights/report/generative-artificial-intelligence-toward-newcivilization
5. https://arxiv.org/abs/2401.01313

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A I FA I L T O C O M P L E T E M O R E
S O P H I S T I C AT E D O R N U A N C E D TA S K S
GenAI algorithms still fail to complete some more sophisticatedor nuanced tasks, and to make predictions when a wide range ofoutcomes is possible, such as the next frame in a video. Image
generation models struggle with complex areas (for example,
generating six-fingered hands or gibberish text). In June 2023,
Amazon deprioritized a number of self-published, AI-generated
romance books that made little to no sense, with titles such as“Apricot barcode architecture” or “When the three attacks”6. Suchexamples of shallowness can be largely addressed by improvements
in training set, size of model, model architecture, and extraneoustechniques (such as reinforcement learning); hence, it can be
expected to diminish in the future.

M A N I P U L AT I O N O F A I S T R E N G T H S
Even if AI were not subject to bias, hallucinations, and shallowness,risks are still associated with how it is used — largely the actual
strength of AI. These relate partly to misuse by bad actors, as well
as a range of safety and security issues.

N E FA R I O U S U S AG E : B L U R R I N G
THE LINES BETWEEN REALITY AND
F A B R I C AT I O N T O C A U S E M I S T R U S T
A N D U N D E R M I N E P E O P L E , C O M PA N I E S ,A N D S TAT E SGenAI is a powerful, easily accessible tool that bad actors canuse to destabilize societies and countries, manipulate opinion, orcommit crimes or breach cybersecurity. It dramatically reduces thecost to produce plausible content, whether text, images, speech, orvideo, which creates a path for bad actors making deepfakes. These
deepfakes can be difficult for the untrained eye to tell from the truth,
which can spread fake news, extortion, and reputational targeting ofindividuals, countries, and organizations.
Deepfake videos posted online increased by 900% from 2020 to 20217,
and are predicted to grow further as AI tools evolve and become more
widely used. Their believability has also improved with the quality ofimage, video, and voice generation. In a recent study, humans had only
a 50% chance of detecting an AI-synthesized face8.
Online influence operations will be transformed by prolific and cheap
content generation. As well as becoming a key weapon in politicalactivities such as elections and military conflicts, online influence isan important tool in commercial marketing and advertising, often inhighly competitive marketplaces. GenAI slashes the cost of producing
propaganda and targeted messaging at scale, attracting more

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6. https://www.vice.com/en/article/v7b774/ai-generated-books-of-nonsense-are-all-over-amazons-bestseller-lists
7. https://www.weforum.org/agenda/2023/05/how-can-we-combat-the-worrying-rise-in-deepfake-content/
8. https://pubmed.ncbi.nlm.nih.gov/35165187/

ARTHUR D. LITTLE“propagandists for hire.” It also enables automation of increasingly
high-quality text and images, including personalization and finetuning to achieve the maximum impact with different audiences.
The fight against bad actors using GenAI has two main strands:	
1. Removal: Deepfake images and videos involving famous people
or covering matters of public concern are swiftly debunked by factcheckers, governments, or software engineers working for media
platforms. This makes deepfakes a costly and relatively ineffective
medium for disinformation purposes. For example, a deepfakeof Ukrainian President Volodymyr Zelensky asking Ukrainians tosurrender to Russian troops, posted on March 16, 2022 on Ukrainian
websites and Telegram, was debunked and removed by Meta,
Twitter, and YouTube the same day.
	
2 . Detection: A wide range of detection technologies have beendeveloped, including lip motion analysis and blood-flow pattern
scrutiny. These boast accuracy rates up to 94%, and can catcha wider range of deepfakes, not just those that involve famous
people. However, most text-based AI detection tools are still fairly
unreliable — with one study placing the best-performing detectors
at below 85% accuracy 9. Already a technology arms race is being
run between AI detection tools and increasingly sophisticatedlanguage models that allow production of harder-to-detect
linguistically distinct messaging.
Despite these potential safeguards, the most lasting impact of
GenAI on information integrity, and one of the greatest risks going
forward, may be to cement a “post-truth” era in online discourse. As
public mistrust and skepticism around online content grows, public
figures can more easily claim that real events are fake. This so-called“liar’s dividend” causes harm to

AS PUBLIC MIS TRUS T AND
S K EP TIC IS M ARO UND O NLINEC O NTENT G ROWS , PUBLICFIG URES CAN M O RE E AS ILY
C L AIM THAT RE AL E VENT S
ARE FAK E .

political accountability, encourages
conspiracy thinking, and further
undermines the public’s confidence inwhat they see, read, and hear online.
The EU AI Act attempts to mitigate
such devastating consequences on
public discourse and democracy bymandating that content creators

disclose whether the content has been artificially generated
or manipulated — but enforcement of this provision remains
challenging.
Mistrust is a risk in terms of customers, the public, and employees.
Public trust in AI varies considerably from country to country, with
developing countries (such as India and China) showing over 80% trust,and developed countries such as Western Europe and Japan showing
35% or less10. Customer mistrust of AI is likely to be an increasing risk
as autonomous customer agents become widespread.

9. https://www.scribbr.com/ai-tools/best-ai-detector/
10. https://policy-futures.centre.uq.edu.au/article/2023/03/survey-over-17000people-indicates-only-half-us-are-willing-trust-ai-work79

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For employees, the introduction of AI is already leading tosubstitution fears, especially among white-collar clerical workers,
who are likely to feel the impact the earliest. In fact, history showsthat new technologies tend to change, rather than eliminate, humanjobs, although some jobs could disappear altogether. Businesses need
to be fully aware of employee trust and labor relations issues prior
to AI adoption and integration and put suitable measures in place tomanage them.

C Y B E R S E C U R I T Y : G E N A I A P P L I C AT I O N S
CAN INCREASE RISKS SUCH AS
P H I S H I N G A N D D ATA M I S U S E
AI-generated content can work in conjunction with social engineering
techniques to destabilize organizations; for example, phishing attacks— attempting to persuade users to provide security credentials —increased by 50% between 2021 and 2022 11 thanks to phishing kits
sourced from the black market and the release of ChatGPT, whichenables creation of more plausible content. Essentially, GenAI
reduces barriers to entry for criminals and significantly decreases thetime and resources needed to develop and launch phishing attacks. It
increases phishing risks in three ways:	
1. M aking coding easier for non-experts, which drives
multiplication of malicious code
2. Making deceptive content more believable and personalized	
3 . Using multimedia generation (for example, fake videos or voices)
to make phishing formats more diverse and unexpected
LLMs can also be manipulated and breached through malicious
prompt injection, which exploits vulnerabilities in the software, often
in an attempt to expose training data. This approach can potentiallymanipulate LLMs and the applications that run on them to shareincorrect or malicious information. Prompt injection can take placethrough the chatbot interface, open source inputs, or training data.
Because of the sheer size of model training sets and the “blackbox” quality of closed source models, identifying malicious intent
in training data will be extremely challenging. The attack surface islarge, and all APIs running on public LLMs are at risk.
Data privacy is another important cybersecurity risk. Publicly
available GenAI tools do not guarantee data privacy, and indeed, thefree version of ChatGPT warns users of this fact. However, OpenAI
guarantees its business customers that it hosts data and conducts
inference on separate Azure servers, thus assuring its security.
Businesses nevertheless are rightly cautious, with many avoiding theuse of public AI altogether (refer to Prism S2 2023 “Taking Control
of AI — Customizing Your Own Knowledge Bots” 12 or establishing
restrictive policies and rules. However, even if such policies are inplace, easy access by any employee to public GenAI tools poses atangible enforcement risk.

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11. https://info.zscaler.com/resources-industry-reports-threatlabz-phishing-report
12. https://www.adlittle.com/en/insights/prism/taking-control-ai

ARTHUR D. LITTLE

Data protection regulations also pose a challenge. For example, in
Europe the GDPR regulations grant individuals the right to insist thatorganizations forget their data. However, GenAI tools do not have thefull ability to remove individual data items from their training dataset.
Businesses using AI remain liable for regulatory violations or harm to
any third parties as a consequence of using GenAI.
Finally, issues with copyright and intellectual property (IP) are wellrecognized. One recent example is the lawsuit the New York Timesbrought against OpenAI in December 2023, claiming the company
had copied millions of the news source’s articles to train its large
language models13. Work is still ongoing to establish whether AIgenerated IP should be subject to the

DATA PROTEC TI O N
REG UL ATIO NS AL SO
P O S E A C HALLEN G E . FO R
E X AMPLE , IN EURO PE THE
G DPR REG UL ATI O NS G R ANTIND IVIDUAL S THE RIG HT TO
INS IS T THAT O RGANIZ ATI O NSFO RG E T THEIR DATA .

same protection as human-generated
IP. Another key issue is whether AI
bots are infringing copyright if theygenerate new works based on training
data that includes existing, protected
works. For businesses, the key risk isinadvertent infringement of copyrightor unauthorized use of IP through using
AI-generated outputs.
Just like the EU AI Act draws on

the provisions of the GDPR for several of its areas, other currently
developing regulations on GenAI are likely to build on top of existingdata regulations and legal frameworks for IP and copyright. This is
likely to include limits on which data can be accessed by AI algorithms
for training, permitted boundaries, standards and risk-levels of AI
applications, and guardrails for allowable AI tools and platforms.

13. https://apnews.com/article/openai-new-york-times-chatgpt-lawsuit-grisham-nyt-69f78c404ace42c0070fdfb9dd4caeb781

P R I S M : B E C A R E F U L O U T T H E R E — U N D E R S TA N D I N G T H E R I S K S O F D E P L OY I N GARTIFICIAL INTELLIGENCE

INSIGHTS FOR THE EXECUTIVE — HOW
C O MPANIES S H O ULD RES P O ND
A vital aspect of successful AI adoption will be careful risk
management. Our experience suggests that the following priorities
will be important for companies.

1 . C A R E F U L LY D E F I N E T H E P R O B L E M
The analytical nature of the problem and its strategic stakes for thecompany should dictate the type of AI, model implementation, andrisk management approach. Asking fundamental questions such as“What are we solving for?”, “What data do we have available?”, and“How much inaccuracy can we tolerate?” helps prevent common
pitfalls such as over-engineering or system scope creep.

2 . I N C L U D E R I S K I D E N T I F I C AT I O N
A S PA R T O F I N I T I A L O P P O R T U N I T Y
LANDSCAPE ASSESSMENT
Companies looking to implement AI will need to start by examining
their relevant business landscape, assessing valuable opportunities,
and implementing proofs of concept. As the opportunities become
clearer, risks associated with these should be systematicallyassessed. For example, some opportunities, such as generation ofadministrative or marketing documentation, could yield high benefits
while being low risk. Others, such as manufacturing, will be muchhigher risk. A robust risk and opportunity assessment approach,including developing a risk taxonomy, assessment criteria, and a risk
appetite statement, will be better able to inform priorities14.

3. IMPLEMENT AI PROCEDURES,
POLICIES, AND TOOLS TO ENSURE
A D E Q U AT E R I S K C O N T R O L
Establishing and communicating a code of ethics for use of AI
provides a robust foundation on which to build. Companies needto consider risks carefully in operational procedures and policies.
Larger companies may benefit more from creating their own training
datasets with customized AI tools. In all situations in which GenAI isused, procedures should ensure that AI outputs are cross-checked andverified. Companies should stay abreast of the latest developments
in AI checking and verification tools, and invest in those that are mosteffective. Ensuring cybersecurity infrastructure and controls are kept
up to date is vital.

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14. “Is AI Still Dumb as a Rock?” ADL Blue Shift Viewpoint, 2023 https://www.adlittle.com/en/insights/viewpoints/ai-still-dumb-rockARTHUR D. LITTLE

4. FOCUS ON TRAINING AND
C A PA B I L I T Y D E V E L O P M E N T
Developing internal capabilities in understanding and implementing
AI is an important part of managing its risks. Developing someunderstanding of how the technology works beyond considering it justa black box is a part of this. Ensuring that executives and leaders also
have enough AI understanding is equally important. Finally, training
employees in identifying misinformation is key.

5. USE GOOD CHANGE MANAGEMENTPR AC TICE IN AI ADOP TION AND
I N T E G R AT I O N
As with all transformations, a well-designed change program shouldbe put in place to manage implementation. A key part of this is tounderstand employee issues around trust and culture, ensure thatthese are adequately addressed, and communicate and engage withstaff. Maintaining a “test and learn” philosophy, starting with lower
risk/more certain applications, is also important. Given the likely paceof development, companies must be able to continuously monitorchanging developments over an extended period. Given the disruptive
potential from AI-generated mis- and disinformation, effective
counter-communication mechanisms and crisis management
processes are critical to avoid destabilizing the organization.
Every transformative technology has both utopian and dystopian
aspects. In the case of AI, the downside risks are significant despite
the huge benefits. Businesses should proceed with caution.

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ARTHUR D. LITTLE

DR. ALBERT MEIGE
is the Director of Blue Shift, Arthur D. Little’s forwardlooking institute, and based in Paris.
ZOE HUCZOK
is a Manager in Arthur D. Little’s San Francisco officeand Program Leader of Blue Shift, the company’s
forward-looking institute.
RICK EAGAR
is a Partner Emeritus of Arthur D. Little, based in
Cambridge, United Kingdom.

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PRISM: CEO INTERVIEW: JEREMY NIXON, OCEAN NET WORK EXPRESS (ONE)“BIG ENOUGH TO SURVIVE
AND SMALL ENOUGH TO CARE —WE CAN DO IT!”

86

ARTHUR D. LITTLEAUTHORS
Yumo Ito, Trung Ghi

AN INTERVIEW WITH
JEREMY NIXONJEREMY NIXONGLOBAL CEO OF ONE

Operating out of Singapore, Ocean Network Express, branded as“ONE,” was formed in April 2018 by merging the three competing
container shipping business units of Japanese parent companies
NYK, MOL, and K-Line. At the time, many commentators highlighted
the challenges of such a large, complex integration. Yet just fiveand a half years later, ONE has become one of the most profitable
and successful companies in the industry, with net income of
approximately US $50 billion over the past five years.
Jeremy Nixon, previously the head of the container division of NYK,
was appointed Global CEO in 2017. He has led ONE from the beginning,steering it through a period of huge change in a volatile environment
including geopolitical tensions, COVID-19, energy crises, and, ofcourse, the ever-increasing pressure to achieve sustainability.
We talked to Jeremy to understand more about ONE’s remarkablejourney since its formation, his perspectives on leading a complex
merger and how human-centric approaches have helped, managing
new technologies, and what the future holds.

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PRISM: CEO INTERVIEW: JEREMY NIXON, OCEAN NET WORK EXPRESS (ONE)TA K I N G U S B A C K T O T H E F O R M AT I O N O FO N E , W H AT C H A L L E N G E S D I D YO U H AV E
TO OVERCOME?
It was a decade of turbulence from the start of 2010 until weformalized the formation of ONE in 2018. Smaller companies
were acquired by larger companies as we began to see a period of
consolidation in the sector. Industry peers such as the Koreans werein difficulties, and actually one of them went bankrupt. The industry
was undergoing a major “shakeup” — a wakeup call for medium-sizedcompanies. You needed to either pivot or sell and get out. That was
how it was back then.

W H AT WA S YO U R V I S I O N A N D S T R AT E G Y
FOR ONE?
ONE was formed by the merger of three Japanese shipping business
units from NYK, MOL, and K-Line, respectively. We are always looking
at ways to find synergies, and therefore looked closely at lessons
learned from NYK, MOL, and K-Line. ONE’s strategy was to rapidly
achieve scale by merging the three container businesses, and thendifferentiate itself with operational efficiency supported by the besttalent and teamwork. All too often, mergers are dominated by simple
headcount and cost reduction.
We operate in over 120 countries, and 80% of our business is handled
by our owned agencies. The container business is a global network
business, and global coverage is key. A lot of companies and people
are involved in delivering one container from origin to destination,such as shippers, vessel“WE OPERATE IN OVER 120
COUNTRIES, AND 80% OF OUR
BUSINESS IS HANDLED BYOUR OWNED AGENCIES.”

operators, terminal operators,
custom authorities, in-landlogistics, warehouse services,and the end customer. To becompetitive in operational
efficiency, we need toconnect all value chains andplayers through collaboration. So we kept talent as a top priority
from the beginning and decided to focus on keeping our best people
as we positioned the company to focus on offering a unique value
proposition to our customers — rather than just trying to compete on
scale with the larger players. We did not aim to be super big. ONE had
good speed to market, and it was lean and agile. We really didn’t wantto have tribalism, and we tried to learn from previous mistakes.
To encourage the best teamwork and collaboration, we implemented
a simplified organizational structure comprising three major divisions:
Corporate (C&I), Product (P&N), and Commercial (M&C). We identified
the most important “best practices” and worked toward applying
these across ONE. We didn’t mind which parent company these bestpractices came from, or even if they came from an external source.

88ARTHUR D. LITTLEW H AT W A S I T L I K E O N D AY 1 ?
Day 1 was April 6, 2018, our “Go live” day. It started simply, with ourstaff “just getting to it”; it was like a call-to-action moment. There
was a good deal of mutual respect, given that many had been in theindustry for a long time. We had customers, a good team, and a good
network, and we wanted to be bold.
That said, the first six months were slow because of some legacy
issues from the three merged companies. In year one, these “teethingproblems” meant we lost money. But from years two to three onwards,
the synergies started to work, and we began to turn the situation
around.

HOW WAS IT DURING COVID -19 ?
COVID arrived two years after Day 1, and we went into it withsome confidence. But, as you might expect, it brought completely
unprecedented challenges to us. For example, our seafarers were
often trapped on their vessels without going ashore. Everyone
remembers the low supermarket stocks and long customer queues,
and maybe, for the first time, people realized the importance ofcontainer shipping as an essential social infrastructure.
But ONE was ready to overcome these challenges. Given the direction
set in year one and the progress we had already achieved, we had good
momentum to keep going and take bold actions where required. Also,
because we were still a young organization, it was a make-or-break
moment, and our people were highly committed and motivated.

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PRISM: CEO INTERVIEW: JEREMY NIXON, OCEAN NET WORK EXPRESS (ONE)HOW DID YOU MANAGE TO CONTINUE
T O M A I N TA I N T H E L O YA LT Y A N D
M O T I VAT I O N O F YO U R P E O P L E ?
Recognition. This is what many staff were excited about. If we had
kept going back to our legacy, we would not have survived. Moving to
a newly established, innovative company is exciting — merging threelegacy companies isn’t!
So we didn’t even mention legacy names. Branding was important. In
fact, “ONE” was a symbol of being “one” company, and the acronym
was re-engineered to encapsulate the business. Ocean Network
Express: “As ONE, We Can.” Even the new company brand color,magenta, was important. In some other M&A cases, legacy colors havebeen kept, and this has created divisions.
The experience of together successfully overcoming the challengesof foundation and integration, closely followed by COVID, establishedquite a strong corporate culture. We have great collaboration andteamwork, and very high employee engagement. This is certainly oneof our strengths.

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ARTHUR D. LITTLEW H AT I S YO U R V I E W O N T H E F U T U R E
FOR ONE?
First of all, we still have room to grow. We have only 6% of global
market share and are not present in all countries. We’re highly present
in east-west trade, but more underweight north-south. Our current
view is therefore to grow intra-regional trade, such as with the Indian
sub-continent, the Middle East, South East Asia, and Latin America.
Sustainable growth is a key part of our longer-term view. This means
contributing value not just to our customers, but also to our broader
stakeholders and society. We see this“IN TERMS OF THE POTENTIALUSE FOR HYDROGEN, WE
SEE IT BEING USED TO FUEL
INDUSTRIES, TO STORE
RENEWABLE ENERGY, AND TO
PRODUCE CHEMICALS.”in three ways: First, decarbonization
is a major focus area. As we werealready part of the Japanese culture,
which recognizes the importanceof being part of nature and a goodsteward of the ocean, we may havefound it easier to make progress
than other companies. There is
now a shared recognition that theindustry has to change, and decarbonization of container shipping
is essential for our customers and the global economy to realize
net zero for Scope 3. A lot of our staff and customers felt strongly
about sustainability, so it was simple for us to accelerate building
sustainability from 2021 onwards. New regulations will come. We needto move quickly since it takes about three years from the order tolaunch a ship that is ready for alternative fuels.

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PRISM: CEO INTERVIEW: JEREMY NIXON, OCEAN NET WORK EXPRESS (ONE)Second, resource growth. To grow, we need people and talent — it’s
simple. During the integration and foundation of ONE, we largely
used seconded staff from the parent companies. Going forward, weneed to focus on building our own talents, recognizing that people’s
expectations in areas such as wellbeing and lifestyle have changed.
We need to adapt to suit.
And third, earnings stability. We need to redefine our business modeland portfolio to be more resilient to global economic and geopoliticalfluctuations. Post-COVID, we had good cashflows, and leveraging this,
we are investing into adjacent, stable earnings businesses along thecontainer shipping value chain, such as ship ownership. This will alsopresent new challenges, such as recruiting people to operate the new
businesses. But we have done this before, and we see setting up a neworganization as exciting given our past experience of setting up ONE.

“I GENUINELY HAVE A PASSION
FOR THE BUSINESS — I LOVECONTAINERS! I HAVE BEEN IN THE
BUSINESS FROM AN EARLY STAGE
AND NEVER SERIOUSLY THOUGHT
OF LEAVING.”

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ARTHUR D. LITTLEW H AT D O YO U S E E A S T H E K E Y S U C C E S S
FA C T O R S I N T H E D I G I TA L A G E ?
A good, strong management team! ONE aspires to become the “digital logistics”
network business, and we recognize that we need to raise our game. So we invest
a lot in AI, digital, etc. However, to make all this“ONE ASPIRES TO BECOME
THE ‘DIGITAL LOGISTICS’NETWORK BUSINESS, AND
WE RECOGNIZE THAT WE
NEED TO RAISE OUR GAME.
SO WE INVEST A LOT IN AI,
DIGITAL, ETC.”

work, we really need strong talent and leadership,
for which a strong brand and culture are essential.
For example, we recently launched the ONE
Academy with four pillars: ONE Communications
to build staff and management communications,
ONE Connectedness to improve teamwork andavoid silos, ONE Learning and Development toboost training and coaching, and ONE Career tohelp incentivize and retain talent. We believe
having good talent and corporate culture arestill key success factors in the age of digital. We need to continue innovating
to remain attractive.

H O W M U C H H AV E T R A D I T I O N A L JA PA N E S E
MODEL S AFFEC TED YOUR HR APPROACH?
It’s true that the Japanese model is known in the West for things such as the“job for life” mentality, with constant job rotation of generalist managers and aperceived “glass ceiling” for staff. But there are good aspects as well, such as thelong-term mindset and prioritizing company value over individual interests. And
the Western style has its own drawbacks, such as a long process to promoteand create successions, too much internal competition, and poor continuityof culture.
Therefore, we have a hybrid model with the best balance for ONE. We have
optimized job rotations, including some designed for specialists as well as
generalists. Our evaluation system has a combined focus on short-term outputs
and long-term development, and emphasizes both individual and team outcomesand performance, including helping others.

W H AT A B O U T YO U R O W N J O U R N E Y ?
I genuinely have a passion for the business — I love containers! I have been in thebusiness from an early stage and never seriously thought of leaving. Everything
is a chapter — you need to refresh yourself every chapter, and you need to do
new things as well as learn from your past. I was lucky to experience two major
M&As in my previous career before ONE, which really helped me to do my bestfor ONE. We need to be hungry to learn, and we need to be very human. I have an
open management style, and I try to explain things in a simple way. We need torecognize good management and remove their roadblocks. I catch up with the top
30–50 management staff every month and always ask them, “What’s stopping
you from being better?” It is about also being fallible: make mistakes, listen to
and learn from people, let others step forward, and be prepared to follow them.

93PRISM: CEO INTERVIEW: JEREMY NIXON, OCEAN NET WORK EXPRESS (ONE)D O YO U H AV E A N Y L A S T C O M M E N T S FO R
OUR READERS?
We are here to make money — but also to build good companies andbe sustainable. I have a phrase that I’ve used and is now framed on myoffice wall behind my desk. Come and let me show you this.

“I HAVE AN OPEN
MANAGEMENT STYLE, AND
I TRY TO EXPLAIN THINGSIN A SIMPLE WAY. WE NEEDTO RECOGNIZE GOOD
MANAGEMENT AND REMOVETHEIR ROADBLOCKS.”AS ONE, WE CAN.
Our company name “ONE” is both a name and a will.
It is the will to become “one” and continue to face the difficulties.
Becoming “one” with customers facing business challenges, it is
our intention to provide a more optimal method for each company.
Becoming “one” with people all over the world.
It is the intention to continue to connect communities witheach other.
We believe in the power of “one” more than anyone else in the world.
Different ideas, different abilities, different cultures.
Combine all differences, bump into each other, and polish them.
From there, new methods are bound to be born.
There are still countless ways to unlock the future ofcontainer shipping.
We can support this world more.
If we become one, we can do it.
JEREMY NIXONGLOBAL CEO OF ONE

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ARTHUR D. LITTLE

YUMA ITO
is a Partner in Arthur D. Little’s Singapore office and amember of the Automotive & Manufacturing practice.
TRUNG GHI
is a Partner in Arthur D. Little’s Singapore office and amember of the Energy, Utilities, & Resources practice.

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