AI Advisory and Professional Services

It’s time to getreal about GenAIin your industry.
Discover the Generative AI
use cases that will deliver realoutcomes, faster with Lenovo
and NVIDIA.

It’s time
for real…
growth,advantage &leadership

Generative AI (GenAI) has captured theattention of industry leaders worldwide,
prompting developers and executives aliketo seek a deeper understanding of how thetechnology can differentiate them in theirchosen markets.
The potential of GenAI lies in making faster
decisions, use of deeper insight and producing
competitive advantages at a pace and cost notpreviously achievable at scale. However, turning
this potential into real-world outcomes demands
a realistic understanding of where GenAI can be
successfully implemented today and the kind ofchallenges that implementation will bring.
While surveys from PwC suggest embedding
new technologies into business models is the
top strategic priority for executives in the next
three to five years, they also suggest that just
48% of CIOs feel prepared as tech leaders to
support new business models. That discrepancy
perfectly describes the situation in whichbusinesses find themselves. They know theyneed GenAI, but don’t quite know where to
start or what their likely barriers will be.

As competitive advantage is driven by
improvements across all functions, from front toback office, it’s only a matter of time until every
aspect of a business will need to be transformed
through use of GenAI.
A race has begun, and it’s those enterprisesthat can understand and adopt GenAI fastest
and in meaningful ways that will prosper mostin the short-term and set themselves up forsustained growth.
With that as our starting point, this guideaims to shine a light on the range of use cases
for GenAI across a business, outline typical
implementation challenges and inspire forwardthinking executives to begin their GenAI journey.
At its heart, GenAI is just a way to accelerateand differentiate businesses – but doing thatmeans coupling the right infrastructure with theright GenAI solution.
That’s the purpose of the Lenovo and
NVIDIA partnership – to create a best-in-breed,
end-to-end offering so customers can get toreal business outcomes, faster.

2

GenAI will generate real outcomes, but the
adoption journey is littered with real barriers…
1

Starting dilemmas:
Businesses often struggle with where
to begin. Identifying quick wins andprioritizing use cases are crucial first steps.

2

Readiness and business case:3

From concept to reality:
Moving from experimentation
to GenAI model production is asignificant hurdle, requiring carefulplanning and execution.

Assessing GenAI readiness and creating
a compelling business case are essential
for obtaining internal support.

Between 2040
and 2060, AI will
have automatedhalf of all work.1$4.4T
value Generative AI
can unlock across key
business functions.1

4 Ethical and secure adoption:

Ensuring responsible and secure
GenAI implementation is not just an
IT concern but a business imperative.

1

McKinsey, 2023, The Economic Potential of Generative AI

3

Getting realwith GenAI
across all yourmajor business
functions

Whether your organization is looking toincrease efficiency, improve experiences,
accelerate innovation or drive sustainability,
the need to adopt GenAI boils down to
one main goal: sustained and increased
competitive advantage.
Almost nine out of every ten CIOs expect
GenAI to reinvent business models, says
PwC. Yet, that suggests that significant
outcome generation from GenAI lies in the
future. That’s almost certainly true, but let’s
not rule out the major difference GenAI canmake today.
However, gaining real advantage
from GenAI today isn’t going to bestraightforward. Building transformational
business systems will place significant
pressure on your IT infrastructure. GenAI
demands huge processing power and theintegration of innovative machine learning(ML), image processing and natural
language technologies into your existingtech stack.

Almost nine out of
every ten CIOs expect
GenAI to reinvent
business models.2
2

PWC, 2023, PwC Pulse Survey: Focused on reinvention

44 key challenges to overcome for GenAI success:Training data
For models to understand, predict and generate human-like text,
organizations need diverse, high-quality and high-volume data.
Customizing pretrained models requires significantly less data thantraining from scratch.
Large-scale infrastructure
The scale of computations needed to train GenAI models from scratch
is immense. It needs robust, large-scale infrastructure, which is expensive
and complex to manage. The compute requirements are significantly lesswhen customizing a pretrained model.
Training and software
Implementing GenAI into applications requires the right hardware anda software stack and tools to overcome both training and inference
obstacles, everything from algorithm development to accelerating
inference on distributed infrastructure.
GenAI expertiseThis new type of solution demands an understanding of at least AI, ML
and data science principles. To build and fine-tune generative models,organizations need to add new technical expertise to their data science,
AI or application development teams.
The good news is that with these barriers overcome, GenAI will deliver
impact and advantage. GenAI’s versatility means it can be deployed
across various business functions, offering both cost reduction andoperational efficiencies.

5

GenAI use cases across some of your business functions
How GenAI can help optimize
IT resources and experiences

Bring automatedaccounting into finance

A GenAI-driven IT solution can drive heightened
productivity across your IT estate or digital
workplace. Hyper-personalized employee
experiences are achievable at a scale and cost notpreviously possible through the power of GenAI.
Employees gain solutions tailored to their needs
whilst computing resource utilization is optimized.

In finance, GenAI supports enhanced fraud
detection and financial forecasting, improving
accuracy and reducing risk, alongsideautomating previously manual tasks.

Benefit
GenAI will optimize tech allocation based on
individual needs and drive new efficiencies
through automation, removing operationalburdens from IT teams, aiding energy
management and empowering businesses
with hyper-personalized employee experiences.

Challenge
Accurately modeling complex resource
allocation scenarios demands significant
training data. Also, insights must be actionable
and not suffer context switching when being
pulled from across the estate or workplace.

Benefit
GenAI can streamline accounting processes,
reduce errors and free up accountants formore strategic tasks.

Challenge
Integrating GenAI into existing accounting
systems and ensuring regulatory compliancewill be complex.

Using predictive
analytics in sales andproduct development
Acceleration is what GenAI can bring to
product development and sales cycles using
analytics to understand demand, expectationand customer timelines.
Benefit
GenAI tools can predict future sales trends
based on historical data, enabling businesses
to optimize inventory, development andmarketing strategies.

Challenge
Data quality and integration of innovative newtechnology with existing sales and marketingsystems will present hurdles.

6

GenAI use cases across someof your business functions
Reaching new levels ofcustomer experience

Optimizing logistics for a
streamlined supply chain

Enhance customer interactions with GenAI,
helping to personalize individual promotional
engagements and making it possible togenerate highly targeted marketing efforts.

With GenAI automating key aspects of the
supply chain, businesses can benefit from better
inventory forecasting, optimize product and raw
material flow, warehousing and distribution andconnect sales and offers directly with supply
and availability.

BenefitWith GenAI enabling personalized interactionsat scale, engagement and loyalty withcustomers will be enhanced.

Challenge
Balancing personalization with privacy andensuring your GenAI model understands diverse
customer behaviors and attitudes.

Benefits
GenAI will optimize delivery routes andschedules, automate real-time alterations
based on demand, reduce fuel costs andimprove delivery times.

Challenges
Implementing GenAI in logistics requires
comprehensive historical and real-time dataon transportation networks and adaptability
to flex around disruptions.

7Getting realwith GenAI for
manufacturing

GenAI will revolutionize manufacturing.
In fact, it’s already begun. A recent survey by
MIT Insights shows how quickly GenAI is being
accepted. In 2022, just 11% of entrepreneurs
thought it a critical supply chain element, yet
predictions for 2025 put the figure at 38%.
The question today isn’t ‘if’ manufacturers will
implement GenAI, it’s how they can overcome
big implementation challenges as they aim forsustained competitiveness and growth.
Alliances are the route for harnessing
innovation so it can properly address
key industry challenges and unlock newopportunities. That’s why Lenovo and NVIDIA
have forged a key strategic partnership.

In 2022, just 11%
of entrepreneurs
thought it a criticalsupply chain element,
yet predictions for2025 put the figure
at 38%.3

3

We understand all needs are different and,as such, the joint aim of our partnership isto help organizations whatever their stageof transformation.
Lenovo AI Advisory and Professional Services
provide a single vendor solution to guidedevelopment and implementation for easily
deployable, purpose-built solutions. NVIDIA AI
Enterprise and our best-in-class ecosystem of
AI Innovators delivers a platform and softwarethat drives differentiation, fuels growth andhelps shape the future of AI-driven solutions.

MIT Technology Review Insights report8Three real world ways GenAI can transform supply
chains (and what needs to be overcome to get there):
Demand forecasting
Benefit
GenAI will predict inventory needs withhistorical, trend and macroeconomic data
to reduce overstocking or stockouts.

Challenge
Integrating GenAI with existing systems
and ensuring accurate predictions acrossdiverse product lines.

Logistics optimization
Benefit
GenAI optimizes delivery routes andschedules to help reduce fuel costs
and improving delivery times.

Challenge
Implementation necessitatescomprehensive transport network data
and real-time adaptability to disruptions.

Supply resilience
Benefit
GenAI predicts and then mitigatesdisruption by using of advanced
analytics to find solutions toproblems that arise.

Challenge
Complex global supply chains and the
dynamic nature of risk create significant
implementation challenges.

And the impact GenAI could
make on smart factories…
Quality checks & predictive maintenance
GenAI will ensure product quality remains
high by using computer vision to checkfor defects and irregularity. It will also help
reduce costs by predicting where and when
maintenance is required and identifying
faults in real time. Training and assistancecan be enhanced with interactive manuals
and guides, while field technicians can use
handhelds to query documentation andinstantly access instructions. However, noneof this is possible without reliable quality
data and integrated systems.
Warehouse & inventory management
With systems correctly integrated,
GenAI will improve inventory accuracy
and operational efficiency with accurate
forecasting and by matching production
to wavering demand, dealing withreturns and picking and packing in realtime. Interactive chatbots for shippers
and receivers, for instance, will surface
documents and info on shipping,customs, tax responsibilities, general
Q&A and more.

9Getting realwith GenAIin retail

Despite growing digital sales and improving
in-store experiences with interactivity andomnichannel services, the outlook in retail lacks
positivity. In fact, a Shopify/Ipsos Commerce
Trends Study highlights big concerns aroundthe impact of inflation, price rises and thesector’s need to reduce costs and be moreagile to cope with growing uncertainty.
The role GenAI will play in retail locations is
to create new possibilities for ever deepening
customer engagement, to build on existing
in-store innovation to drive interest and sales.
Alliances are the route for harnessing
innovation so it can properly address
key industry challenges and unlock newopportunities. That’s why Lenovo and NVIDIA
have forged a key strategic partnership.
We understand all needs are different and,as such, the joint aim of our retail partnershipis to help organizations whatever their stageof transformation.
Lenovo AI Advisory and Professional Services
provide a single vendor solution to guidedevelopment and implementation for easily
deployable, purpose-built solutions. NVIDIA AI
Enterprise and our best-in-class ecosystem of
AI Innovators delivers a platform and softwarethat drives differentiation, fuels growth andhelps shape the future of AI-driven solutions.

10Creating unique,personalized
in-store experiences
for shoppers
By harnessing the power of
GenAI, retailers can ensure
store-level edge computing
is a critical component of theirdigital evolution. Advanced
cameras, custom softwareand easy-to-use dashboards
will empower retailers to know
customers as well in-store
as online.
That means gaining and using
real time insights in eachindividual store to informproduct placement and pricing
decisions, inventory planningand even crime prevention
measures. GenAI can enhance
experiences with features likedesign assistants, voice-enabled
search, review summaries andsmart recommenders that
understand context.

Understand customers better

Enable frictionless shopping

BenefitComputer vision coupled with store analytics willturn visual info on shoppers’ reactions, behavior
and movements into rich data for marketers.

Benefit
Automated, scan-free stores will revolutionize
payments – long queues and mistakes will be
replaced with walk-in, walk-out shopping experiences.

Challenge
Capturing the right data and turning that into
usable insights to inform personalized marketing
and real-time offers and insights for staff.

Challenge
For computer vision to change retail requires
perfect data training, capture and recognition
for seamless experiences.

Optimize prices dynamically

Smart inventories & quality control

Benefit
Automatically update prices based on any numberof factors – such as demand, location, stock levels,
offers from rivals or even the weather.

BenefitTrack products by using cameras to scan for empty
shelves or misplaced, out of date and damaged
items to enable efficient restock and reordering.

Challenge
Establishing a robust, scalable system isn’t easy –it needs real-time processing, quality data, multiple
sources and integration with existing technology.

Challenge
Infrastructure must gain real-time data and compare
it to historical data to determine an appropriate
course of action for maximum efficiency.
11

Getting realwith GenAI infinancial services

51% of financial
service executives sayachieving measurable
value from new tech isa challenge.4

4Technology is both the strategic priority
and biggest pain point for financial services.
The sector must stay relevant, competitiveand present a robust defense against
cybercrime, yet at the same time onboarding
new solutions, innovating and making thatwork within an existing tech stack is achallenge that won’t go away.
According to a recent PWC study, 51% of
financial service executives say achieving
measurable value from new tech is a challenge.
When it comes to GenAI, the potential for
discernible ROI is compelling, but the firstchallenge to be overcome lies in understanding
all the many and varied ways it can be used
and the implementation barriers that standin the way.
Alliances are the route for harnessing
innovation so it can properly address key
industry challenges and unlock newopportunities. That’s why Lenovo and NVIDIA
have forged a key strategic partnership.

Financial transformers, or “FinFormers”, canlearn context and understand the meaning of
unstructured financial data. They can power
Q&A chatbots, summarize and translatefinancial texts, provide early warning signsof counterparty risk, quickly retrieve data,and identify data-quality issues.
These generative AI tools rely on frameworks
that can integrate proprietary data into modeltraining and fine-tuning, integrate data curation
to prevent bias, and add guardrails to keep
conversations finance specific.
Lenovo AI Advisory and Professional Services
provide a single vendor solution to guidedevelopment and implementation for easily
deployable, purpose-built solutions. NVIDIA AI
Enterprise and our best-in-class ecosystem of
AI Innovators delivers a platform and softwarethat drives differentiation, fuels growth andhelps shape the future of AI-driven solutions.

We understand all needs are different and,as such, the joint aim of our partnership isto help organizations whatever their stageof transformation. For example, we can help
enterprises make use of domain-specific andproprietary data attuned to their applications.

PwC Pulse Survey, August 22, 2023

12

Four real world ways
GenAI can transformthe front office(and what needs
to be overcome
to get there)

In-branch facial recognition

Enhance recommendations

BenefitPrevent unauthorized account access without theneed for customers to authenticate with ID cards
or passwords.

Benefit
ML recommendation systems can help
advisors make suggestions faster, better
and with more accuracy.

Challenge
A new layer of sensitive biometric data only
increases the pressure for secure networks
and communications.

Challenge
Connecting multiple data sources for a ‘real time’view and to make all necessary data available
to advisors.

Elevate CX & WX with chatbots

Automate claims processing

Benefit
Save people time with instant and accurate
responses. Ease stress, enhance productivity
and satisfaction.

BenefitStreamline and automate routine processes
like data entry, document verification andeligibility checks.

Challenge
Ensuring responses are natural, brand aligned
and offer accurate advice requires a wealth oftraining data.

Challenge
Integrating data from diverse sources andnew technology with legacy systems toensure interoperability.

13And in the back officeEnhance risk prevention

Automate compliance management

Automated document processing

Benefit
Identify, assess and mitigate risk withenhance pattern identification, real-timemonitoring and predictive analysis.

Benefit
Automating data gathering for regulatorycompliance and extract insights from
corporate disclosure.

Benefit
Automate whole workflows from data
extraction without error. Sort, categorize
and route appropriately.

Challenge
Real-time processing requires low latency,
while new technology needs integrating
and multiple data sources.

Challenge
Interoperability with other legacy
compliance systems is necessary forcreation of new, seamless workflows.

Challenge
Need to centralize, protect and clean datafrom disparate systems for consistency,
quality and easy access.

Better fraud detection

New product innovation

BenefitGain minimized false positives, realtime detection, behavioral analysis andadaptability for evolving threats.

BenefitAnalyze markets, customers andcompetitors to understand opportunities
faster, personalize and validate.

Challenge
Building a robust architecture that unifies
storage, processes in real-time, scales anduses ML to streamline.

Challenge
Training and running complex models
demand investment in high-performancecomputing infrastructure.
14

Getting realwith GenAIin education

Tech adoption in education is complex. The sector is awash withmajor challenges around digital literacy, prohibitive costs andconcerns around privacy and security. Yet, it’s widely recognizedthat GenAI can have transformative impact on learning and thattechnological evolution is a necessity.
From personalized learning to helping tutors with grading, GenAI
has the capacity to enhance the quality of education and remove
much of the drudgery and needless repetition. However, ensuring
GenAI is used ethically and transparently will be a vital piece of
the implementation jigsaw.
The key question for educators today is how they can overcome
the main implementation challenges as they aim for better student
outcomes and experiences. Universities can train chatbots to
support students with general information, registration, financial
aid and more. At the same time, researchers can automate
experiments, collect data, create synthetic data for model training
and conduct data analysis.
Alliances are the route for harnessing innovation so it can properly
address key industry challenges and unlock new opportunities.
That’s why Lenovo and NVIDIA have forged a key strategic
partnership in education.
We understand all needs are different and, as such, the joint aimof our partnership is to help organizations whatever their stageof transformation.
Lenovo AI Advisory and Professional Services provide a single
vendor solution to guide development and implementation foreasily deployable, purpose-built solutions. NVIDIA AI Enterpriseand our best-in-class ecosystem of AI Innovators delivers aplatform and software that drives differentiation, fuels growthand helps shape the future of AI-driven solutions.
15

Three real world ways GenAI can transform student
experiences (and what needs to be overcome to get there)
Adaptive learning systems
GenAI can personalize
experiences for individual
students, changing in real-time
to suit performance and learning
style and providing customized
resources and learning paths.

Automated grading
and assessment
GenAI algorithms can
automatically grade work –everything from multiple-choicetests to complex assignments,
such as essays.

Engagement andperformance analytics
GenAI tools can analyze dataon student interaction andperformance to provide insights
on their engagement andlearning progress.

Benefit
Improved engagement, better
understanding of complex
subjects and accommodationof different learning speeds
and styles.

Benefit
Reduced workload on educators,
allowing them to focus more on
high-value teaching to ensure
embedded learning and less timeon admin tasks.

Benefit
Educators can easily identify
students who need extra support,then ensure interventions aretimely and appropriate andtailored to the individual.

Challenge
Ensuring these systems areaccessible to all students andmaintaining data privacy requires
high-performance computation
and robust architecture.

Challenge
Ensuring fairness and accuracy,
particularly for subjective
assignments, recognizing andmanaging potential biases in
GenAI algorithms.

Challenge
Balancing data-driven insights
with personal interactions andmaintaining the privacy of
individual students is of
critical importance.

16

Using GenAI to streamline
further in the classroom
and across campus
GenAI can bring rapid evolution across a range ofeducational use cases, including the introduction of
automation into the classroom to relieve teachers andadministers from mundane, repetitive tasks and improve
the overall student experience. For example:• Automated attendance systems can use students ID
cards or facial recognition software to identify them,making the process quicker• Intelligent scheduling can optimize planners, avoid
clashes and maximize utilization of classrooms andother learning environments• Real-time language translation resolves the issueof students from various linguistic backgrounds
attending a lecture

Want to put reliable
tech in the hands ofyour students andteachers – with security
as standard?
Find out more about our end-to-end
services and how they’re designed toenable safe, accessible learning and to
spark the imagination.
To maximize everyone’s potential,
Lenovo is committed to continuous
innovation that anticipates and meets
tomorrow’s challenges.
Discover more

• Using cameras and GenAI to monitor school or
campus premises to detect unusual activities orunauthorized access
GenAI can also be used to automate campus
management workflows, curriculum development
and even provide AI-powered tutor support andself-service tutoring for students.

17

Getting realwith GenAI inlife sciences &healthcare

Of the many varied uses of GenAI, it’s impact on the healthand wellbeing of our friends, families and communities could
be the most profound. At an industry level, the economic
impact of GenAI could also be startling, as it tidies theinefficiency that has long mired the sector. Goldman Sachs
says it takes eight years and $2 billion to develop a drug
– and only one in ten candidates is expected to then gain
regulatory approval. That’s a lot of waste.
These two key aspects of health create an enormous
opportunity for uses of GenAI and ML to improve andaccelerate diagnostics, community care, drug development,telehealth and treatment outcomes. In fact, there are GenAIuse cases for almost every aspect of healthcare, so thequestion today around GenAI is how quickly the sector will
overcome its main implementation challenges and start toreap the potential benefits.
Alliances are the route for harnessing innovation so it canproperly address key industry challenges and unlock newopportunities. That’s why Lenovo and NVIDIA have forgeda key strategic partnership.

700+

Algorithms approved for use
by FDA, as of December 2023.5

5

We understand all needs are different and, as such, thejoint aim of our partnership is to help organizations
whatever their stage of transformation.
Lenovo AI Advisory and Professional Services provide
a single vendor solution to guide development andimplementation for easily deployable, purpose-built
solutions. NVIDIA AI Enterprise and our best-in-classecosystem of AI Innovators delivers a platform andsoftware that drives differentiation, fuels growthand helps shape the future of AI-driven solutions.

 ealth Imaging, 2023, FDA has now cleared 700 AI
H
healthcare algorithms, more than 76% in radiology

18

In the real world, GenAI is alreadytransforming healthcare

Unlocking much-needed efficiencies
in life science development cycles:

From chatbots to virtual assistants, remote patient monitoring, natural
language processing for health records, GenAI can transform care andimprove processes in a sector burdened by chronic inefficiencies.

In everything from clinical trial management and recruitment
to drug discovery, demand, pricing and revenue management,
GenAI can have a profound impact on life sciences. None moreso than a much-anticipated reduction of the traditionally highcosts of drug development and its often-lengthy timelines.

Benefit
Better outcomes with real-time insights and predictive diagnosis thatenable early intervention and/or prevention, reduce waiting times
and ensure faster treatment. Shorter management time and resource
allocation optimization will lead to improved efficiency and costeffectiveness, while also enabling staff to spend more time with patientsand less on lower priority tasks or those that can be automated.

Challenge
A lack of standardized infrastructure is as much or a barrier inhealthcare as in other sectors, which leads to compatibility issues.
Of course, training and running GenAI effectively demands highperformance computing and good quality data, from multiple sources,
whereas health data is often inconsistent and/or inaccurate. Critically,
there is the need to safeguard patient data and ensure responsible
and transparent use of GenAI.

Benefit
Enabling synthetic data generation and fast tracking early-stage discovery
with molecular docking. GenAI’s predictive analytics and recommendations
will also evaluate viability, potential side effects of drug candidates and help
assess the repurposing of existing drugs for new treatments.

Challenge
Patient data protection will require enhanced surveillance systems.
Continuous education will be needed for professionals on use of newtechnologies, while concerns that AI/ML models may be susceptible
to bias will need to be overcome to build trust and reliability in newworking methods.

19

It starts today– real andsustained
growth from
Generative AI
Your four criticalconsiderations on theroad to real-world
GenAI adoption are…

1

4

Can you develop a strategic plan for scaling
GenAI built around use cases that drive
strategic business outcomes?

Generative AI is new. It demands
knowledge of AI, ML and data science.
To build and fine-tune GenAI models,organizations need new expertise.
Selecting the right partners will bringcertainty and clarity.

Start small, plan big

2

Build, buy or outsource
Will you develop in-house solutions,purchase or outsource to an expert team?

Choose the right partner

That’s why we have forged our strategic
GenAI partnership. Lenovo AI Advisory
and Professional Services provide
the single vendor solution to guide
implementation and easily deploy
purpose-built solutions. NVIDIA AI
Enterprise delivers a platform that drives
differentiation, fuels growth and helps
shape the future of AI-driven solutions.

3

Beyond technology
Can you consider data, people
and processes as one entity?

20

How we help create real outcomes with GenAIWith our best-in-class software innovation, AI Advisory and Professional Services and cutting-edge
infrastructure, Lenovo and NVIDIA accelerate GenAI implementation and deploy next-level solutions.
Together, we offer five services to support every step of your AI journey:
Click tolearn more

Step 1
AI Discover

Step 2AI Advisory

Step 3
AI Fast Start

Step 4
AI Deployand Scale

Step 5AI Managed

AI Discover
Identify your GenAI vision
What should you prioritize? What would fit your business needs? What’s secure and scalable?
Here’s how we help:• Work hard to understand your organization and offer solutions that fit
your GenAI maturity.
• Outline key objectives and use cases to support your vision for GenAI.
• Create a clear vision for GenAI in your business and 360º visibility on what
it takes to get there – from strategic planning to implementation.

21

The vision is yours.
Get there with Lenovo
and NVIDIA
Ready to find out how we
can help, whatever your
GenAI maturity? Let’s arrange
a discovery session with
one of our experts…
Book an AI Discover Workshop.