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AI in Africa:
Unlocking Potential,
Igniting Progress
A working paper
September 2023

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AI in Africa: A working paper - 1

Contents
1. Foreword............................................................................................................................................................ 1
2. Introduction..................................................................................................................................................... 3
3. The socio-economic opportunity of AI in Africa: Sizing the value for select economies.. 4
3.1 Transforming consumer-facing industries
3.2 Re-imagining the future of agriculture
3.3 Enabling financial inclusion across communities
3.4 Personalizing education
3.5 Democratizing access to healthcare
3.6 Widening the reach of public services

4. Developing and deploying AI responsibly: Myths and risks surrounding AI..................... 10
4.1 Tackling the myths associated with AI
4.2 Tangible AI risks that need to be mitigated

5. Harnessing the potential of AI for Africa: Potential steps for policymakers to consider... 15
5.1 Human capital: Preparing the workforce for AI
5.2 Supporting next-gen technologies: Create avenues for industry engagement
5.3 Regulatory ecosystem: Promote a proportionate, risk-based approach to govern AI

6. Appendix: Methodology............................................................................................................................ 17
Endnotes................................................................................................................................................................ 19

This report has been prepared by Access Partnership in partnership with Google. All information in this report is derived or estimated by Access Partnership analysis using publicly available
information. Google has not supplied any additional data, nor does it endorse any estimates made in the report. Where information has been obtained from third-party sources andproprietary research, this is clearly referenced in the endnotes.
Access Partnership (https://accesspartnership.com/), is the world’s leading public policy firm dedicated to opening markets for technology. We shape national, regional, and international
policies to ensure a fair, long-lasting environment for technology that drives growth. Our teams in six offices across the globe uniquely mix policy and technical expertise to drive outcomesfor clients operating at the intersection of technology, data, and connectivity.
Access Partnership’s Economics Strategy team (formerly known as AlphaBeta) is a leading economic and strategy consulting practice with deep experience across a number of topics
in the digital economy and the future of skills, sustainability, and economic development. It works with the public sector, corporations, NGOs, not-for-profits and investors to identify
opportunities and develop strategies to grow, improve service delivery, support economic prosperity and generate tangible impact.
Copyright [C] 2023. The information contained herein is the property of AA Access Partnership Limited and is provided on condition that it will not be reproduced, copied, lent, or disclosed,
directly or indirectly, nor used for any purpose other than that for which it was specifically furnished.
AA Access Partnership Limited

2 - AI in Africa: A working paper

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1. Foreword
Some challenges that are present today in
Artificial Intelligence (AI) development are
helpfully unambiguous: African stakeholders
and the international community must
conspire to make it possible for AI to drive
economic growth and unleash new formsof economic opportunity on the continent.
This is an exciting time in AI development,
especially with the emergence of large
language models like Google’s PaLM2 andOpen AI’s GPT-4, which forms the foundationof generative AI. The general-purpose
nature of this technology is key: the same
technology that can help predict natural
disasters and speed up cancer research
can also generate massive productivity
gains and catalyze economic development.
But to capitalize on this promise, forwardthinking policymakers and those that seek toestablish sound AI policies must have a plan
to harness AI, starting in the macroeconomic
environment.
AI is already being used to address a wide
range of African and global humanitarian
challenges, from predicting floods andearthquakes and improving maternal healthoutcomes, to protecting endangered species
and safeguarding food security. All of thisfoundational scientific work must now beapplied to the urgent task of economic
development in Africa. AI can help improve
productivity and job outcomes acrosssectors like manufacturing, agriculture,
financial services, and natural resources thatare key to African economic growth. And
we are seeing Africa’s entrepreneurs andbusinesses begin to harness AI across a wide
variety of domains.
This paper highlights specific opportunities
and challenges for the wider African society
to leverage AI and leapfrog ahead, driving
economic and social growth. We believethat emerging economies, including African
economies, have the potential to sprint
ahead in achieving sustainable economic
gains through digital transformation.

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AI in Africa: A working paper - 1

1. Foreword

As with any transformational technology,
AI comes with complexities and risks
which are still evolving as the technology
develops and uses evolve and expand.
Therefore, we believe that getting AI right for
Africa must be a collective effort between
the technology industry, researchers,
governments, entrepreneurs, businesses,
non-profit organizations, and citizens topromote responsible use and mitigate
risks. Policymakers and industry must be
focused on mitigating risks from AI andbuilding public trust as they are to unlock
productivity benefits and prepare African
entrepreneurs and traditional industries
to harness AI. A comprehensive agenda on
opportunity, responsibility, and security isneeded to drive African AI leadership. This
paper aims to address the knowledge gaps
about the impact of AI in Africa, in line with
our mission to ensure that everyone hasaccess to transformative technologies, suchas AI, while promoting fair competition andconsumer choice.
We know from experience that by pursuing AI
boldly and responsibly, AI can deliver on thepotential to assist and improve the lives ofpeople in Africa (and everywhere else). And weare excited – determined – to invite thoughtsfrom the readers as we continue to build
a deeper analysis of the opportunities andchallenges for AI on the world’s youngest and,by extension, the most promising continent.

Gregory Francis,

CEO, Access Partnership2 - AI in Africa: A working paper

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2. Introduction
The term Artificial Intelligence (AI) was coinedin 1956 by John McCarthy, a cognitive scientist
and Stanford computer science professor, who
proposed the possibility of replicating human
intelligence “so precisely...that a machine can bemade to simulate it”. The concept of AI builds
on this pioneering idea, generally referring tocomputer software that “learns” from data,
behaves intelligently, and mimics humancognition and perception. As such, AI covers awide range of models and processes, including“deep learning,” “machine learning” and “natural
language processing”, that depend on the useof large amounts of data to train software inpatterns and create corresponding outcomes. In
this paper, we refer to AI as a catch-all term fortechniques that enable computers to learn fromdata and behave intelligently, especially thosethat integrate machine-learning techniques,
including deep learning.
The latest wave of AI innovation anddeployment has the potential to betransformational by not only changing the very
nature of how technology advances throughaccelerating scientific breakthroughs, but also
by creating new economic opportunities andjobs never thought of before. Technologicalshifts, such as the printing press, the industrial
revolution, electrification, and the internet
have a history of driving social and economicchanges – both positive (such as higher living
standards, reduction of disease and mortality,
alleviation of extreme poverty, and increased
quality of life) and negative (disruption,
inequality, and insecurity).
As we stand at the threshold of the generative
AI revolution, it will be critical to take early steps
to harness the power of AI to improve economic
capabilities for regions like Sub-Saharan Africa. AI
will be critical to Africa’s future socio-economic
growth, enabling current and future generationsof Africans to live in a more prosperous, healthy,
secure, and sustainable world. At the same time,
AI, if not developed and deployed responsibly as
part of an integrated tech and economic agenda,
also presents significant risks.

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This paper aims to take stock of what wecurrently know (and don’t know) about thepotential societal and economic impacts of AI in
Africa and provide the foundation for a discussion
with key stakeholders across the government andbusiness sectors to chart the way forward.
In this paper, we cover the potential benefits of
AI for Africa (Section 3) as well as the myths andrisks associated with AI (Section 4). Realizing the AI
innovation potential requires a holistic AI strategy
that focuses on unlocking opportunities throughinnovation and inclusive economic growth,
ensuring responsibility and trust, equipping
traditional industries with skills and partnerships
to harness AI, and protecting socio-economic
security. The final section of this paper seeks tobring these ideas together into a concrete set ofpolicies and actions African governments can taketo drive adoption of responsible AI in a way that is
consistent with economic goals (Section 5).
It is important to note that this paper provides
an initial assessment of AI’s potential role indriving economic growth. Ideas generated fromdiscussions around this paper will be incorporated
in a future report, which will provide acomprehensive assessment of economic benefits,
key risks, and detailed policy recommendations
for emerging markets looking to capitalize on AI
development and deployment.

An AI representation of Dr. John McCarthy, distinguished cognitive scientist
and Stanford professor, working on his computer.

AI in Africa: A working paper - 3

3. The socio-economic opportunity of AI in Africa:
Sizing the value for select economies
Africa’s population is exceptionally young
compared to other world regions: only 3% of
sub-Saharan Africa’s population is over 65
while a staggering 44% are below 14, compared
to 18% and 17% respectively among OECD
countries.1 This “demographic dividend” could
be a major driver of future economic growth,
but only if the region tackles its low level oflabor productivity. A recent World Bank study
found that productivity, as measured byoutput per worker, has lagged in Africa evenas other developing countries have achievedvarying but steady gains in productivity.2 In
contrast, Africa’s labor productivity trajectoryhas been influenced largely by commodity
price movements, and has not experienced
sustainable improvements. While boostingproductivity requires a multi-faceted approach,including tackling issues ranging from property
rights through to education reform, digitaltechnologies such as AI can be an importantlever in closing the productivity gap.
AI can play a key role in improving subSaharan Africa’s economic growth, not only
by enhancing productivity and job outcomes
across a wide variety of sectors, including
agriculture, manufacturing, education, andhealthcare, but also by improving creative
processes and generating new leapfrogging
opportunities. These sectors have the potential
to move up the value chain as companies
can begin to produce more complex andvaluable products and services enabled by
AI. Both large and small businesses, as well
as workers of all skill levels, have a strong
opportunity to derive significant benefits fromthe wider adoption of AI applications. For
example, larger organizations would be able
to automate procedure-based processes thatwould require significant work hours, whilesmaller businesses may be able to accesscomplex data analysis at scale. Workers
themselves would also benefit from having
mundane tasks being automated, leaving them

4 - AI in Africa: A working paperwith more room and time for other excitingand essential work. At the same time, it iscritical to acknowledge that societies will faceinevitable disruptions and potential costs asthey transition to AI. As more tasks incorporateAI, new skills will be needed and some skills
will become redundant, requiring investments
in upskilling and reskilling.
What is the potential size of this value inAfrica? Providing a “top-down” estimate of AI’s
benefits to African economies is difficult given
the wide scope of different AI applications.
Instead, this research takes a “bottom-up”
approach, focusing on a set of specific AI
applications in key sectors of Sub-Saharaneconomies to understand the potential
benefits. This paper provides a preliminary
estimate, and by no means is an exhaustive
estimate of the potential benefits brought by
AI. Still, the potential impact is staggering.
A preliminary assessment by Access
Partnership estimates (details in the
appendix) that AI applications could support
up to USD136 billion worth of economic
benefits for four sub-Saharan countries(Ghana, Kenya, Nigeria, and South Africa) by
2030, based on current growth rates andscope of analysis (Exhibit 1).3 To put this inperspective, this figure is higher than Kenya’s
current GDP and represents 12.7% of the2022 GDP for these four economies. This
number represents incremental benefits toeconomies (measured in terms of economic
benefits such as cost savings or revenue
gains) in 2030 in a scenario where therelevant AI applications are fully adopted, as
compared to a state of no AI adoption.
In the following sections, we describe someof these benefits in key areas such as
consumer, retail & hospitality, agriculture,
financial inclusion, education, healthcare, andpublic services.

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3. The socio-economic opportunity of AI in Africa: Sizing the value for select economies

3.1 Transforming consumer-facing industries
Consumer-driven industries, especially retail,food and accommodation, provide much needed
goods and services to the general population.
With its wide reach, this sector has a strong
opportunity to capture significant economic
benefits offered by digital technologies, including
AI. However, limited modernization constrains
its ability to deliver higher quality of services tocustomers. For example, in Nigeria, 97% of retailsales are driven by small, traditional open-air
kiosks while 77% of retail goods sold in Kenya
are bought from similar types of stores.4
South Africa is relatively modernized withmodern supermarkets representing around
70% of retail sales – however, e-commerce isstill relatively nascent, accounting for just 1.3%of retail sales as of 2020.5

Retailers and other consumer-facing
businesses, especially smaller-sized ones,
can leverage AI to boost their reach as well as
improve their cost-effectiveness. For example,
through digital marketing tools coupled with
AI-driven analytics, businesses can leverage
historical customer patterns and trends toidentify potential new customers. Such tools
tend to be provided either free or at relatively
low cost, making them accessible to mostsmall and medium-sized enterprises andenabling them to expand their reach. Google
Ads, one of many online tools that businesses
can use, provides AI-powered digitalmarketing solutions such as creating targeted
advertising campaigns to online users.6 To
drive the adoption of such tools, Google
also launched Google for Small Businessfor African businesses, which provides free
PRELIMINARY

Sub-Saharan Africa could gain up to USD136 billion worth of economic
benefits from AI in 2030
Potential annual economic value from AI applications, by sector1
5.9
USD billion, 2030
0.1
8.0
Ghana

South Africa

Kenya

8.5

Nigeria

9.1

9.8

11.8

20.0

2.1 0.7

2.4 0.6
2.7
6.1

0.3
1.6
5.6
2.3

0.1
0.7
5.8
2.4

0.9
2.8
3.2
1.7

0.5
0.2
5.0
2.3

0.4
3.4
2.0

3.8

0.1
0.7
0.7 2.4

3.7

2.1

0.2
0.5
0.5 2.6

0.1
1.2 0.5
0.3

136.2
7.8
17.2

52.2

9.3

22.8
1.6

30.7

7.8

2.0 1.0

18.2

59.0

3.3
3.4
9.4

14.6

Total
Consumer, Agriculture
Retail && FoodHospitality

Manufacturing

Infrastructure

Financial
Services

Professional
services

Mobility

Resources

Other
services

Education& Training

HealthGovernment

1. These estimates do not represent GDP or market size (revenue), but rather economic impact, including productivity gains, cost savings, time savings, and increased revenues. AI
applications refers to two groups of applications: (1) Conventional applications of AI, such as analytics-driven tools in marketing and sales or operational-centric efficiencies inmanufacturing that could arise from predictive maintenance and improved manufacturing yields from optimization; and (2) Generative AI, which involves the use of applications that are built
upon foundation models and neural networks, which include capabilities to process and model outputs such as images, video, audio, and computer code.
Note: These are preliminary estimates. Numbers may not sum due to rounding.

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SOURCE: Access Partnership analysis

AI in Africa: A working paper - 5

3. The socio-economic opportunity of AI in Africa: Sizing the value for select economies

courses on how to use digital marketing tools.
Other technology companies have also or areplanning to provide digital resources to small
businesses. AI technologies also support thehospitality industry by enhancing customer
experiences through chatbots or virtualassistants that can address queries or maketravel bookings instantaneously. Overall, AIbased technologies could bring up to USD30.7
billion worth of economic impact by 2030
to Kenya, Ghana, Nigeria, and South Africa’s
consumer, retail, and hospitality sectors.
3.2 Re-imagining the future of agriculture
Agriculture accounts for 17.3% of sub-SaharanAfrica’s gross domestic product (GDP) andsupports the livelihood of more than half ofthe employed population, almost twice theglobal average.7 Despite this, more than 60%of the region’s population is experiencing
food insecurity at a moderate or severe level8,
reflecting symptoms of poor agricultural yieldand harsh climatic conditions, an issue that
requires even more urgent attention given theexacerbating effects of climate change. SubSaharan Africa could double its agricultural
output by improving the yield and reducing
postharvest loss, improving food security andreducing the region’s dependence on foodimports.9
AI can help alleviate such challenges byenabling improved crop yields, better weather
forecasting, the research and development of
new drought-resistant crops, and supporting
optimization of water use. Our initial estimatessuggest that such applications could support
up to USD23 billion of economic impact by
2030 should farmers in Kenya, Ghana, Nigeria,
and South Africa adopt and deploy thesetools. One example of leveraging AI in the
agriculture business is AI-powered drones
that monitor crops for pests and diseases,
and AI-powered algorithms can help farmers
to make better decisions about planting,

6 - AI in Africa: A working paper

harvesting, and irrigation – improving crop
yields and boosting agricultural productivity.
Mineral - X, for example, uses AI to build theworld’s first detailed “operating manual” forplants to promote sustainable agriculture
by bringing together diverse sources of
information that until now were simply toocomplex or overwhelming to be useful.10
Lastly, the Pan-African research organization
AKADEMIYA2063 developed the Africa
Agriculture Watch (AagWa), a web-based toolthat uses AI and satellite sensing to aid the
production of staple foods including maize,
cassava, and sorghum across 47 African
economies.11 The application forecasts andmonitors the production and yield of key
crops based on imaging and machine learningalgorithms, enabling stakeholders to manage
their agricultural output in times of crisis or
upswing. These AI applications distill a wide
range of information to formulate practicaladvice for smallholder farmers, especially intimes of crisis.
3.3 Enabling financial inclusion acrosscommunities
Financial inclusion remains a key issue forthe sub-Saharan African region. 45% of the
population (aged 15 and above) remained
unbanked in 2021, despite the spread of mobile
phones that could enable digital wallets andmoney transfer products such as M-Pesa.12
Informal economies and cash transactions
continue to dominate financial activities – forexample, 65% of all South African payments
remained cash-based in 2022, despite 85%of the population being banked.13 Finally, only
between a third and a fifth of small-to-medium
enterprises (SMEs) in the region have a bankloan or line of credit.14 High transaction costs
and low levels of financial literacy continue toimpede broader financial access.
AI technologies can be used to develop
new financial products and services thataccesspartnership.com

3. The socio-economic opportunity of AI in Africa: Sizing the value for select economies

AI-powered creditworthinessanalysis has the potential tosupport and expand access tofinancial services, especially forsmaller businesses.
are accessible to people in low-income
countries. For example, AI-powered financial
advisors are expected to bring greater financial
literacy and provide better quality of services
to low- and middle-income countries,
including marginalized communities that areoften disproportionately unbanked in thesecountries. AI-powered creditworthinessanalysis can support the issuance of microloans to help small businesses grow, while
AI-powered underwriting supports insurance
provision to help people protect themselvesfrom financial shocks. Google’s anti-money
laundering AI applications, featured in its
cloud-based tools, enable banks to detectsuspicious activity while minimizing false
positives, creating efficiencies for investigation
teams.15 Banks in Africa are also investing in AI,
with the African Development Bank providing
around USD1 million to the national banks of
Ghana and Rwanda as well as the consumer
watchdog agency in Zambia to establish AIdriven customer management systems.16
Overall, AI-based technologies could potentiallybring up to USD10 billion worth of economic
benefits to Kenya, Ghana, Nigeria, and South
Africa.
3.4 Personalizing education
Educational development in the region
continues to improve, but existing gaps provide
strong opportunities for AI to accelerate thispace. For example, while the literacy rate
among the adult population has improved
from just 59% in 2010 to 67% in 2020, it isstill significantly lower than the global rate ofaccesspartnership.com

87%.17 In Nigeria, the most populous country
in sub-Saharan Africa, around 20% of primaryschool children drop out of education as of2020, signaling a gap in education provision.18
Today, sub-Saharan Africa has almost thesame number of tertiary graduate enrolments
as Brazil, a country with 1/6th the population of
the region.19 One of many factors contributing
to this trend includes the lack of personalized
attention given to struggling individuals,
especially for those from less privileged
backgrounds.
AI can play a strong role in bridging the literacy
divide through the use of text and visual-toaudio applications. Read Along, Google’s AIbased reading tutor app and website that canhelp track and correct reading skills is one ofmany tools the deployment to support child
literacy. Over the past three years, more than
30 million kids have read more than 120 million

Read Along provides support tochild literacy through Diya, thein-app and AI-enabled reading
buddy which listens and tutors
pronunciation for speakers.
stories on Read Along. AI can also be used topersonalize learning, provide real-time feedback,and assess student progress. For example,
AI-powered tutors can help students to learn
to read or how to do math equations at theirown pace, and AI-powered assessments canprovide teachers with insights into student
learning. AI-enabled analytics can also support
educators by automating repetitive evaluations,administration, and lesson preparation –Schoolinka, a Nigeria-based ed-tech firm, helps
teachers evaluate children’s literacy levels andcurate personalized learning curriculums.20
AI’s potential can be maximized by addressing
some of these gaps in connectivity, such as the

AI in Africa: A working paper - 7

3. The socio-economic opportunity of AI in Africa: Sizing the value for select economies

lack of access to mobile or Internet devices
and promoting data affordability in Africa.
3.5 Democratizing access to healthcare
Access to healthcare services remains
stratified across populations, mainly due toa lack of expertise or talent. More than 400
million in sub-Saharan Africa lack immediate
access to healthcare.21 This trend differs
across countries – at least half the populationof Chad and Somalia do not have accessto healthcare, and close to 20% experience
the same challenge in South Africa. Lack ofinvestments in infrastructure and low levelsof productivity of healthcare institutions could
be key reasons for this trend, alongside thelimited reach of healthcare services in rural
areas.
AI-powered algorithms can help to deliver
more services to a broader population by
expanding access to effective diagnosis andtreatment provided by specialists. For example,
AI-powered medical imaging can help doctors
identify diseases more accurately and provide
timely intervention – including doctors whomeet their patients remotely. Instead of
traveling to city centers, patients living in rural
areas can go to their local clinics to receive

Google’s partnership with
Jacaranda Health is expected toenable practitioners who haveminimal expertise on traditional
ultrasound machines to stillplay a role in maternity care.
By simply sweeping a handheld
probe across the mother’s belly,
they would be able to acquire
and interpret ultrasound images
and triage high-risk patients.

8 - AI in Africa: A working paper

specialist treatment, as local nurses can send
information on scans and assessments tophysicians living thousands of miles away. AIpowered platforms can assist these physiciansin diagnosing these faraway patients, evensending to other doctors for separate opinions.
Another potential use case is the early
detection of possible infections, such as theuse of AI to identify likely tuberculosis (TB)
patients for follow-up testing.22
3.6 Widening the reach of public services
Governments in sub-Saharan Africa havemade significant progress in public service
delivery, particularly in e-governance – theUN’s E-Government Development Index
indicates that the continent has doubled
its performance score from 0.2 in 2003 toalmost 0.4 in 2020.23 Despite that, the figure
is still below the world average of 0.6 in 2020,
showing that sub-Saharan Africa still has a long
way to go.
AI technologies can be used to underpin
essential public services as well as operations.
For example, AI-enabled analysis of tax records
can detect fraud and evasion more effectively
than traditional methods of transaction
monitoring, anti-money laundering (AML) or
due diligence (DD). Cloud technologies arealso expected to support deployment of AI
technologies, as public service agencies canupload data onto cloud servers and leverage

During the pandemic, thegovernment of Togo used machinelearning to analyse satellite
imagery, enabling it to identify
geographic areas with vulnerable
populations that required urgent
economic support.

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3. The socio-economic opportunity of AI in Africa: Sizing the value for select economies

off-site computing power processes remotelyfor AI-driven analytics. These agencies canharness their massive amounts of data to
train machine learning models and identify
patterns or issues, from detecting potholes
for municipal-level issues, to helping fileunemployment claims. Provision of public
services to citizens can also be made more
efficient through AI-powered chatbots which
can address open-ended questions online.
Natural-language processing and translation
tools can also expand access to publicaccesspartnership.com

resources, especially for populations that
exclusively speak local languages or dialects.
Lesan, an Ethiopia-based startup, actively
helps to collect and curate local language
content to train and build translation tools toenable readers to access a wider variety ofcontent online.24 These tools could potentiallybe used to translate governmental content
into other ethnic languages – a use case that
could prove to be useful in language-diverse
countries, such as South Africa, which has 12
official languages.

AI in Africa: A working paper - 9

4. Developing and deploying AI responsibly:
Myths and risks surrounding AI
The pace of AI research breakthroughs is now
being matched by real-world applications,offering new possibilities for boostingproductivity and insight across virtually every
field. At the same time, AI is shining a new lighton old and difficult questions. Therefore, it is

crucial to study the impact of AI on society.
However, there has been limited research
focused on Africa on several key AI-related
topics (Table 1), creating a need to conduct
deeper research to understand local impact
and inform decision-making.

Table 1: Overview of existing research to date
Impact on
employment

Impact on productivity

Societal impact

Risks (including privacy)

Broader Africa

Limited research

Existence of headline
reports such as How is AI
being utilized in Africa? byStrathmore University

Existence of headline
reports such asState of AI in Africa
by AI Media Group

Limited research

Ghana

Limited research

Limited research

Limited research

Limited research

Kenya

Limited research

Existence of headline reports
such as AI in Kenya by
Paradigm Initiative.

Limited research

Existence of headline
reports such as AI in Kenya
by Paradigm Initiative.

Nigeria

Limited research

Existence of headline reports
such as AI for Economic
Development in Nigeria by
Citris Policy Labs

Limited research

Existence of headline
reports such as AI for
Economic Development in
Nigeria by Citris Policy LabsSouth Africa

Reports such as The
Future of Work in South
Africa by McKinsey & Co
(2019)

Limited research

Limited research

Limited research

Country/region

Legend: No color – Limited coverage, Amber – Some coverage, Green – Extensive coverage

4.1 Tackling the myths associated with AI
This lack of evidence of the impact of AI in
the African context is one of many reasonsfor concerns amongst African policymakers
regarding AI. While some concerns are justified,based on the existing analysis in Africa andelsewhere, it is worth challenging some of these
beliefs. This section covers the top three myths
associated with AI.

A

AI and its impact onjobs in Africa

AI enables the automation of certain tasks
and roles, creating a perception that AI could
displace many workers and create large
employment losses. However, AI is more likely to

10 - AI in Africa: A working paper

augment human capabilities and skills, enhance
productivity, create new job roles, and eventransform existing ones. At the same time, withadvances in AI technologies, AI will allow human
workers to focus more on higher-value activities
that require creativity, critical thinking, emotional
intelligence, and problem-solving skills.
For example, a recent study25 concluded
that occupations in the US that are more
exposed to AI experience no visible impact on
employment – the study found that AI-exposed
establishments created new tasks whilesubstituting human labor in a subset of tasks.
A similar study in Europe found that AI-enabled
automation leads to job creation for high-skill
occupations and younger workers.26 Preliminary
research covering Africa also suggests thataccesspartnership.com

4. Developing and deploying AI responsibly: Myths and risks surrounding AI

artificial intelligence could have a strong positive
impact on employment27. Similarly, generative
AI will change the focus within jobs, rather thanreplace them entirely – and there is potential
for most workers to use generative AI to somedegree in their work28. For example, our recent
studies estimated that in India, Indonesia, and
the Philippines, almost half of the workers
will potentially use generative AI for between
5-20% of their regular work activities - in effect,
unlocking USD621 billion (India), USD243.5 billion(Indonesia), and USD79.3 billion (Philippines) in
productive capacity in these emerging markets.
However, the actual impact for a particularsector or country will depend on factors such as
the economic mix of the sector/ country, paceof technological development, the adoption of
AI by businesses, the skills of the workforce,and the policies of governments. Therefore,
governments have a critical role to play inthis space to ensure that the jobs market is
impacted positively. There is also a need to
conduct more research to contextualize theimpact of AI on the African jobs market.
AI will also change the way jobs are foundand done. For example, AI could lead to more
efficient job market matching, which leads tolower unemployment. AI has vastly expanded
the range of time- and resource-saving
possibilities when screening and shortlisting
candidates, drafting job descriptions andimproving job portals. However, it is key to notethat AI adoption can only be successful with afocus on reskilling and upskilling programs toadapt the workforce to the evolving job market.
This will ensure that AI will not only create jobs
for the highly skilled but will benefit a wider
spectrum of job roles.

B

AI for SMEs andindividuals in Africa

AI’s reach is no longer restricted to only large
corporations. Major strides in AI tech mean thata broad spectrum of organizations and people

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can now tap into its potential. While some highlevel AI technologies might incur substantial
costs and demand significant resources, arange of AI implementation options exist.
Not every approach necessitates substantial
budgets or extensive resource allocation. The
democratization of AI has ushered in a new
era where open-source tools, libraries, andframeworks are available, enabling resourceconstrained organizations to leverage AI’s
potential. For example, Open Health Stackprovides building blocks for creating next-gen
healthcare apps, which provide secure, offlinecapable, data-driven solutions for healthcare
workers in low-resource settings.29
Additionally, cloud-based AI services havedemocratized access further by rendering
AI usage more cost-effective and feasible
for enterprises, even without substantial
infrastructure investments. Notably, cloudservice providers offer an array of AI tools andplatforms, making it possible for businessesof all scales to harness AI capabilities. By
capitalizing on cloud-based Software-as-aService (SaaS) and Machine Learning-as-aService (MLaaS), small and medium enterprises(SMEs) can achieve scalability of AI solutions ina cost-effective manner, with the added perkof not requiring extensive technical know-how.
In addition, inherent digital security features are
woven into the software, ensuring a safe andsecure digital footprint.
AI’s transformative influence spans acrossdiverse sectors, including healthcare, finance,
agriculture, manufacturing, and education.
With a smart approach to harnessing AI,
emerging markets are uniquely poised toreap the technology’s economic, productivity,and competitiveness benefits – helping
level the playing field with larger players inmore established markets. AI applications
could allow a medium-sized company, say in
Ghana, to compete with large conglomerates
in established markets, such as the US,

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4. Developing and deploying AI responsibly: Myths and risks surrounding AI

Germany, or China, by gaining access tosome of the same production, distribution,and market analysis tools that were once theexclusive provenance of the largest global
conglomerates. While those larger global
companies will also see productivity gains
from AI, the most significant economic gains
and productivity enhancements from AI
could occur in emerging markets. Africa could
achieve large gains from AI due to a larger
pool of younger workers (who are more likely
to adopt AI30 and are already familiar with AI
and other technologies) and lower burdenof organizational legacy infrastructure that
impedes the ability to adopt, experiment,
and iterate with AI technologies — making iteasier to leapfrog established players in many
economic sectors.

CAI, privacy, and security
in Africa

Since AI systems rely on large data sets forlearning, there is concern about the collection
and processing of personal and sensitive
data (such as medical and financial). Besides
concerns about data breaches, there is also
concern about how AI tools (such as facialrecognition, hiring algorithms) and generative
AI tools (such as generating misinformation)
could create potential privacy issues. Similarly,
there are concerns that bad actors withaccess to AI will be able to launch cyberattacks more frequently. All of this could
impact economic output – cybercrime
reduced GDP within Africa by more than 10%,at a cost of an estimated USD 4.12 billion in
202131.
In reality, AI also has the potential to enhance
privacy and security measures. AI can beused to develop robust security systems,
detect anomalies, and protect sensitive data.
However, responsible AI development anddeployment requires careful consideration

12 - AI in Africa: A working paperof privacy safeguards and ethical principles,such as data minimization, transparency, anduser consent. There is also potential for AI
to improve cybersecurity of businesses andindividuals by better predicting and detecting
threats. It provides faster responses to thecybersecurity incidents, ultimately reducing
the cost of data breaches for businesses.32 For
example, in a recent study, we estimated thatcosts associated with cybersecurity risks inAustralia can be reduced by 49% in 2030 fromthe deployment of AI and online cybersecurity
training33.
4.2 Tangible AI risks that need to be
mitigated
AI can be a powerful driver of progress that
boosts Africa’s socio-economic growth, just as
it holds the capacity to amplify existing societal
issues. To ensure the responsible adoptionof AI and exploit its benefits to the fullest,
governments should remain vigilant about therisks like the social and digital divides arisingfrom inequitable access to the technology,
malevolent misuse aimed at confounding
and fragmenting society, and the absence ofstructured support to guide SMEs on their path
toward digital transformation.

A

Social divide due tolack of skills

One of the foremost challenges in Africa’s
AI adoption is the potential exacerbation of
the current social and digital divides. As AI
technologies become more prevalent acrossindustries, their benefit could inadvertently
favor segments of the population withmore resources and access to technology.
A sizeable portion of Africa’s population stilllacks access to quality education and digital
infrastructure, exemplified by the continent’s
internet penetration rate of 36% - merely
half of the global average.34 Limited internet

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4. Developing and deploying AI responsibly: Myths and risks surrounding AI

connectivity and inadequate educational andfinancial support produce disparity in Africans’
opportunities to learn and hone the technicalskills needed to utilize AI tools and services.
The adoption of AI then could marginalize
those who are unable to acquire the relevant
skills to engage with AI systems, thereby
further excluding the already excluded.
In order to ensure the benefits of AI
technologies are equitably distributed andfoster social inclusion, African countries
need to focus on enablers of sustainable AI
adoption, viz., infrastructure, data ecosystems,
technical skills and education, andgovernance.35 As of 2023, no country in Africa
has yet been able to reach the G20 thresholdfrom 2011 for the level of digital skills36. This
would require access to reliable networks,
affordable data, and accessible devices.
African countries will also need to focus onbringing AI education to local communities

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at all levels of education. This would include
specialized programs, such as classroom
programs focused on school-going populations
and AI upskilling for the working population, togeneral digital literacy programs for the broader
population.

B

Challenges to information quality andabuse by bad actors, including mis- or
disinformation

While AI-driven systems can enhance accessto information and promote communication,
there are also known limitations in ensuring
they are consistently accurate, robust, andrepresentative. Models may sometimes
misrepresent facts or inaccurately identify
insights. For some topics, there are data voids,that is, there isn’t enough reliable information
about a given subject for the model to learn
about it and then make good predictions. In
these cases, we see an increase in low-quality

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4. Developing and deploying AI responsibly: Myths and risks surrounding AI

or inaccurate information generation. Gaps,
biases and stereotypes in training data canresult in a model reflecting those in its outputs
as it tries to predict a plausible response. Thisis a known challenge across large language
models (LLMs), and reinforces the importanceof robust approaches to testing.
Even more concerning is the potential for
malicious misuse by bad actors. This same
incredibly beneficial technology could
be misused by bad actors to produce
disinformation or deep fakes. During anelection, for example, AI-generated fakeimages of candidates have the potential
to mislead voters and undermine theintegrity of the electoral process. This is
not a new phenomenon. Kenyan journalists
have found how easily manipulated social
media algorithms could be with deliberatecampaigns by the “disinformation-for-hire”
industry.37 Similarly, there have been cases of
misinformation spreading during the recent
elections in Nigeria38. With over 40 elections
planned till end of 2024 in Africa39, it remains
critical to support multiple approaches totackling misinformation and disinformation.
This includes voter education, helping votersfind authoritative information about theelection, ensuring campaigns have strong
security protections in place; protecting
platforms from abuse; and investing in factchecking. AI tools can be helpful to this effort.
For example, Full Fact, a UK based organization
fighting misinformation through fact checking
and campaigning, has been developing AI
fact checking technology since 2015 to help
increase the speed, scale and impact of fact
checking40.

14 - AI in Africa: A working paper

C

Lack of mechanisms to onboard SMEs
on AI transformation journey

Small-and-medium enterprises (SMEs)
form the backbone of the African economy,
accounting for 95% of all registeredbusinesses and about 50% of the total GDP
in sub-Saharan countries.41 Their importanceto African economies suggests that theirsuccessful integration of AI can significantly
influence overall economic growth. For
example, AI can supplement SME skills (e.g.,
simplifying financial management, automatingstock management) and potentially
improve their business performance andsustainability. However, many SMEs facebarriers when attempting to embark on thedigital transformation journey – let alone themore unfamiliar path of an AI transformation
journey. Limited access to resources,
technical expertise, and financial constraints
can hinder their adoption of AI tools andprocesses. By 2040, Africa is poised to havethe world’s largest working-age population.
Preparing for their seamless integration andabsorption into the workforce hinges on thecreation of quality jobs.42 A starting point
for this endeavor can be equipping African
SMEs with digital and technological fluency
so that the opportunities presented in them
can attract the continent‘s burgeoning poolof young talent. To do so, SMEs need anenabling environment that provides them withessential stepping stones to venture into theirdigital transformation journeys.

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5. Harnessing the potential of AI for Africa:
Potential steps for policymakers to consider
To fully unlock AI’s economic potential in Africa,
governments must take a forward-leaning
approach to adopting and deploying AI while
ensuring that workers are equipped with abroad set of skills that enables them to adapt
to an AI-driven economy, and that downside
risks are mitigated. Governments themselves
must also procure and use AI tools in a way thatshows other industries in emerging markets
how to harness AI for economic growth.
Google’s Digital Sprinters framework provides
guidance to key policy and business actions
to capture the benefits of emerging digitaltechnologies, including AI. The framework
includes four pillars:

1

2

3

4

Creating physical capital byenhancing connectivity to theinternet and digital infrastructure

Uplifting human capital byinvesting in people through talentand skills development

Building a regulatory ecosystemthat promotes competitive andopen markets.

Accelerating technologicalinnovation and supporting
the growth of next-generation
technologies, mainly artificial
intelligence and cloud computing

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All four pillars call for reforms and greater
investment by governments and the private
sector to harness the potential of AI and thebroader digital transformation.
This paper does not attempt to provide
a comprehensive set of policy actions toenable AI in each country or across eachpillar. Instead, suggests prominent highlights
to interesting areas being pursued in othercountries to mitigate the three risks that may
help inform the approach locally.
5.1 Human capital: Preparing the workforce
for AI
It is imperative that African countries invest
in capacity-building of the labor market in
conjunction with infrastructure development
to maximize the benefits of AI when thestage is ready. Enhancing the AI preparednessof the workforce will require building upondigital literacy first and then fostering digitalfluency in AI. In recognition of the importanceof digital literacy and the danger of a widening
digital divide, India has rolled out the Pradhan
Mantri Gramin Digital Saksharta Abhiyann(PMGDISHA) initiative, which provides training
to rural households so that at least one
person in every family can be digitally literate.43
Indian Prime Minister Narendra Modi has
also committed to upskilling the workforce
in advanced technologies and processes,
which will necessitate cross-government
efforts to update educational and vocational
policies.44 Similarly, President Bongbong Marcosof the Philippines also issued a directive toreview and update the school curriculumin ways that primary and secondary school
education can help lift the digital literacy ofstudents. In the Philippines, the governmentis currently developing a skills framework for
AI and data analytics to map out the sectorspecific and cross-sectoral skills that will
be required of an AI-enabled workforce.45
Recently, the National Information Technology

AI in Africa: A working paper - 15

5. Harnessing the potential of AI for Africa: Potential steps for policymakers to consider

Development Agency (NITDA) in Nigeria
launched a series of trainings and lectures
to develop programming skills in Artificial
Intelligence and Machine Learning throughNational Centre for Artificial Intelligence andRobotics (NCAIR), in conjunction with Google
Developers Group (GDG), to benefit 1,227
beneficiaries across 10 cohorts46.
The implication for policymakers in Africa
is that they should consider prioritizing thedevelopment of comprehensive training
and education programs in partnerships
with academia and industry leaders. These
programs could target various segments ofthe population, including vulnerable groups,
to bridge the digital divide and empower
all citizens with the ability to apply andleverage AI technologies across a variety ofsituations. As done in many countries in SSA,
policymakers could continue to explore ways
for cross-sectoral collaboration to develop
online courses and platforms for upskilling.
5.2 Supporting next gen technologies:
Create avenues for industry engagement
Policymakers should leverage resourcesand expertise from a broader set ofstakeholders, such as industry, academia,
and civil society, and invite them to actively
foster an inclusive AI ecosystem, highlightingthat it would be mutually beneficial. To
do so, regular channels of communication
should first be established between thegovernment and these stakeholders to
identify concerns and practical approaches
to address them. Once these are identified,policymakers can facilitate partnerships
between these stakeholders and SMEs,
providing mentorship, technical assistance,
and funding to those seeking to adopt anduse AI technologies. An example of this is
the Google for Startups Accelerator: Africa
program, which started in 2018 to support

16 - AI in Africa: A working paper

the startup ecosystem. Other measuresof society-wide support that can help
SMEs onboard AI technologies in theirservices and operations include creating
and running focus groups comprising
SMEs at similar stages of business growth,where they have access to peer feedback
and support, supplemented by consulting
from larger companies. These concerted
efforts can create a favorable ecosystem
where the symbiotic relationship between
larger corporations and SMEs advances
the responsible and equitable adoption ofAI, leading to overall economic growth andtechnological progress across the African
landscape.
5.3 Regulatory ecosystem: Promote a
proportionate, risk-based approach to
govern AI
African policymakers should consider
delineating the fundamental componentsof AI governance as a first stride toward
developing robust regulatory frameworks.
There is a momentum towards developing
such AI frameworks in Africa; for example,
the African Union’s AI Continental Strategy
and Nigeria’s National AI Strategy are being
drafted. Pursuing proportionate, riskbased approaches can enable responsible
development and application of nextgeneration technologies. It also requires
careful consideration of the trade-offs
between different policy objectives, including
efficiency and productivity enhancement,
transparency, fairness, privacy, security,
and resilience. This will require a multistakeholder approach, wherein government
agencies, tech and legal experts, andcivil society come together to establish
a balanced regulatory environment. An
exemplary blueprint for AI governance thathas been produced in coordination withindustry is the White House Commitments

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5. Harnessing the potential of AI for Africa: Potential steps for policymakers to consider

for AI risk management.47 Developed together
with leading AI companies, such as Amazon,
Google, and Microsoft, the commitments
are based on the three principles ofsafety, security, and trust and outline theresponsibilities of AI stakeholders acrossvarious stages of technology development
and deployment. Kenya and Nigeria have
conveyed their endorsement of thesecommitments, confirming the need for andrelevance of such a framework in Africa’s
context.
This could also be accelerated by building
consensus and capacity across governmentsin Africa. There is a need for dialogue inAfrica at a continental level to take the proinnovation AI policy agenda forward and forthe private sector to come together to build
capacity for governments.
Through this paper, we aim to establish thecontext for the role AI can play in Africa’s
economic transformation, and the need tobuild an ecosystem to enable AI adoption.
We invite thoughts from the readers as we
continue to build a deeper analysis of theopportunities and challenges for AI in Africa.

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AI in Africa: A working paper - 17

6. Appendix: Methodology
The total economic value of benefits from artificial
intelligence (AI) was estimated through an evaluationof the economic benefit that comes from various
AI applications across multiple industries in an
economy.
AI applications refer to tools built upon advanced
analytics techniques that rely on artificial neuralnetworks. The resultant use cases of these tools
vary across industries and business functions. For
example, businesses may derive benefits towardpricing and product promotion, where AI-enabled
analytics assist businesses to model optimal productprices as well as to support the identification oftargeted marketing collateral and recommendations
to consumers. Goods-producing industries, suchas manufacturing, may also be able to extend thelifespan of machinery and assets through AI-assisted
predictive maintenance, relying on time series data
and as well as analogue data points (including audio
and imagery from sensors) to identify bottlenecks or
system failures. A specific segment of AI applications,called generative AI, refers to applications built upon
foundation models, spanning different data types
and modalities, including images, video, audio, andcomputer code. Generative AI is unique in that theresultant models are able to classify, edit, summarize,
answer questions, and draft content – in essence,
generate output, as compared to conventional AI
which assists in analytics-driven assessments.
A three-step methodology was used to understandthe potential economic impact created by AI and
AI-powered technologies in 2030.
Step 1 included review of several existing research
reports on current and emerging AI technologies
to identify the most relevant technologies to focus
on for this analysis in terms of their potential
economic impact. There is a large body of researchby academics, development practitioners, non-forprofits as well as the private and public sector on
the interaction between technologies and economic
development. For example, in 2018, ITU produced areport estimating the impact of over 400 potential
use cases of AI on the firms. Similarly, in 2023, weanalyzed the impact of generative AI at national level18 - AI in Africa: A working paper

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6. Appendix: Methodology

for Asian countries by analyzing over 2,000 work
activities. McKinsey Global Institute also analyzed 63
generative use cases in a 2023 report. A database of
impact of these use cases and AI technologies wascreated using this literature review, which built on ourpast work for the Digital Sprinter reports for Google.
Step 2 was to map the relevant impact assessments
and estimates to the 12 focus sectors and theirsources of economic value. Economic value refers
to increased value created from a scenario of full
adoption of these applications across the entire
economy, and includes impacts such as increased
revenue or profits, improved productivity, or increased
quality. For example, AI-enabled weather monitoringand precision agriculture technologies are associatedwith providing productivity impacts to the Agriculture
and food sector, while applications that driveincreased sales and revenue of retail purchases due
to AI-powered targeted advertising are associatedwith increasing revenue within the Consumer,
retail, and hospitality sector. In general, impact
estimates were generalized into percentage-based
revenue increments for each sector. (E.g., based on
this mapping exercising and review of literature, AI
applications are estimated to generate an incrementof up to 3.7% in revenue for the Agriculture andfood sector in a scenario of full AI adoption acrossbusinesses).
Step 3 was to derive the industry-level impact for
the 4 focus countries based on the derived potential
sector revenue increments from using AI. Industry
revenues for each economy were derived based onnational accounts data, which provide sector-level
GDP estimates and output-to-GDP ratios. Sector
level revenues were then multiplied with theirrespective AI-impact estimates, (I.e., we calculated
the impact of AI on Nigeria’s Agriculture and foodsector based on its sector revenues multiplied withthe estimated 3.7% revenue impact assessed in Step
2). These estimates were then aggregated to produce
economy-level estimates.

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AI in Africa: A working paper - 19

Endnotes
1

The World Bank, 2022. Retrieved in September 2023.

2

The World Bank (2002). Boosting Productivity in Sub-Saharan Africa:
Policies and Institutions to Promote Efficiency. Available at: https://
openknowledge.worldbank.org/entities/publication/a47a77b1-2ca751ed-8fef-cb4a9f0460fa/full

3This analysis refers to two groups of applications: (1) Conventional applications of AI, such as analytics-driven tools in marketing and sales
or operational-centric efficiencies in manufacturing that arise frompredictive maintenance and improved manufacturing yields from
optimization; and (2) Generative AI, which involves the use of applications that are built upon foundation models and neural network,
which include capabilities that cover models for images, video, audio,
and computer code. Details of the approach are in the appendix.

4

Boston Consulting Group (2022), “The future of traditional retail in
Africa.” Available at: https://www.bcg.com/publications/2022/the-future-of-traditional-retail-in-africa

5

Accenture (2020), Unlocking digital value for South Africa’s consumer
industry. Available at: https://www.accenture.com/_acnmedia/PDF116/Accenture-Unlocking-Digital-Value-South-Africa-Consumer-Industry.pdf

6

Google (2023), “Introducing a new era of AI-powered ads with Google.”
Available at: https://blog.google/products/ads-commerce/ai-powered-ads-google-marketing-live/

7

The World Bank, 2022. Retrieved on 21 August 2023.

8

UNICEF (2022), The State of Food Security and Nutrition in the World
2022. Available at: https://data.unicef.org/resources/sofi-2022/

9

McKinsey (2019), Winning in Africa’s agricultural market. Available at:https://www.mckinsey.com/industries/agriculture/our-insights/winning-in-africas-agricultural-market

10 X (2023), Mineral. Available at: https://x.company/projects/mineral/
11 AKADEMIYA2063 (2021), “Artificial Intelligence and Satellite Remote
Sensing Data for Decision-making in the African Agricultural Sector.”
Available at: https://akademiya2063.org/press_releases/Africa_Agriculture_Watch_Brochure.pdf
12 The World Bank (2023), Global Findex Database. Available at: https://data.worldbank.org/indicator/FX.OWN.TOTL.ZS?locations=ZG
13 Euromonitor (2023), “The Normalisation of Mobile Money in Sub-Saharan Africa.’ Available at: https://www.euromonitor.com/article/
the-normalisation-of-mobile-money-in-sub-saharan-africa
14 Center for Strategic & International Studies (2021), “Supporting
Small and Medium Enterprises in Sub-Saharan Africa throughBlended Finance.” Available at: https://www.csis.org/analysis/
supporting-small-and-medium-enterprises-sub-saharan-africa-through-blended-finance
15 Google, “Anti Money Laundering AI.” Available at: https://cloud.google.
com/anti-money-laundering-ai
16 African Development Bank (2021), “African Development Bank
provides $1 million for AI-based national customer management
systems in Ghana, Rwanda and Zambia.” Available at: https://www.
afdb.org/en/news-and-events/press-releases/african-development-bank-provides-1-million-ai-based-national-customer-management-systems-ghana-rwanda-and-zambia-42602
17 The World Bank (2023), Literacy rate, adult total. Available
at: https://data.worldbank.org/indicator/SE.ADT.LITR.ZS?locations=ZG-1W
18 UNESCO (2023), Global Education Monitoring Report. Available at:https://education-estimates.org/completion/country/
19 The World Bank (2023), Enrolment rate in tertiary education, adulttotal. Available at: https://data.worldbank.org/indicator/SE.ADT.LITR.
ZS?locations=ZG-1W

20 - AI in Africa: A working paper

20 Koop, W. and Thomsen, B.S., World Economic Forum (2023), “How AI
can accelerate students’ holistic development and make teaching more fulfilling.” Available at: https://www.weforum.org/agenda/2023/05/ai-accelerate-students-holistic-development-teaching-fulfilling
21 UNDP (2020), “A chance for universal healthcare in sub-Saharan Africa.” Available at: https://www.undp.org/blog/chance-universal-healthcare-sub-saharan-africa
22 Google (2021). Tackling tuberculosis screening with AI. Available
at: https://blog.google/technology/health/tuberculosis-screening-ai-io-2021/
23 Tony Blair Institute (2022), “Digital Government in Sub-SaharanAfrica: Evolving Fast, Lacking Frameworks.” Available at: https://www.institute.global/insights/tech-and-digitalisation/digital-government-sub-saharan-africa-evolving-fast-lacking-frameworks
24 DW (2023), “Bridging the AI language gap in Africa and beyond.” Available at: https://www.dw.com/en/bridging-the-ai-language-gap-in-africa-and-beyond/a-66331763
25 Journal of Labor Economics (April 2022), Artificial Intelligence andJobs: Evidence from Online Vacancies, Daron Acemoglu, David Autor,
Jonathon Hazell, and Pascual Restrepo. Available at: https://www.
journals.uchicago.edu/doi/10.1086/718327
26 CEPR (2023), Artificial intelligence and jobs: Evidence from Europe,
Stefania Albanesi, Antonio Dias da Silva, Juan Francisco Jimeno, Ana
Lamo, Alena Wabitsch. Available at: https://cepr.org/voxeu/columns/
artificial-intelligence-and-jobs-evidence-europe
27 International Journal of Research and Innovation in Social Science(April 2023), The Impact of Artificial Intelligence on Employment:
Evidence in Africa, Frederick Forkuo Yeboah. Available at: https://doi.
org/10.47772/IJRISS.2023.7487
28 Access Partnership (2023), The Economic Impact of Generative AI:
The future of Work in India. Available at: https://accesspartnership.
com/the-economic-impact-of-generative-ai-the-future-of-work-inindia
29 Open Health Stack (2023), Accelerating the future of digital health.
Available at: https://developers.google.com/open-health-stack
30 NBER (2022), Advanced Technologies Adoption and Use by U.S. Firms:
Evidence from the Annual Business Survey. Available at: https://www.
nber.org/papers/w28290
31 Interpol (2020), African Cyberthreat Assessment Report. Available at:https://www.interpol.int/en/content/download/16759/file/AfricanCyberthreatAssessment_ENGLISH.pdf
32 IBM (2021), Cost of a Data Breach Report 2021. Available at: https://www.ibm.com/downloads/cas/ OJDVQGRY
33 Access Partnership (2022), Google’s Economic Impact in Australia. Available at: https://accesspartnership.com/googles-economicimpact-in-australia-helping-build-australias-digital-future-through-technology/
34 Statista (2023). Global internet penetration rate as of July 2023, byregion. Accessible at: https://www.statista.com/statistics/269329/
penetration-rate-of-the-internet-by-region/
35 Centre for Intellectual Property and Information Technology Law(2023). The State of AI in Africa Report 2023. Available at: https://cipit.
strathmore.edu/wp-content/uploads/2023/05/The-State-of-AI-in-Africa-Report-2023-min.pdf; Davis, Tara et al. (2022). AI Governance inAfrica: an Overview of Regulation and Policy Work on Artificial Intelligence in Africa ALT Advisory. Available at: http://ai.altadvisory.africa/
36 Brookings Institution (2023). Digitalization and Digital Skills Gaps in
Africa: An empirical profile. Available at: https://www.brookings.edu/
wp-content/uploads/2023/05/Bhorat-et.-al-May-2023-Digitalizationand-digital-skills-in-Africa-1.pdf

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Endnotes

37 Mozilla (2021). Fellow Research: Inside the shadowy world of disinformation-for-hire in Kenya. Available at: https://foundation.mozilla.org/
en/blog/fellow-research-inside-the-shadowy-world-of-disinformation-for-hire-in-kenya/
38 BBC (2023). Nigerian elections 2023: False claims and viral videos
debunked. Accessible at: https://www.bbc.com/news/world-africa-64797274
39 EISA (2023). Election Calendar 2023. Available at: https://www.eisa.
org/election-calendar/
40 Google.org (2023). Nigerian fact checkers fight election misinformation with Full Fact’s AI Tools. Available at: https://blog.google/intl/
en-africa/company-news/technology/nigerian-fact-checkers-fightelection-misinformation-with-full-facts-ai-tools/
41 World Economic Forum (2023). Why Africa’s SMEs need more thanmoney to ensure their growth. Accessible at: https://www.weforum.
org/agenda/2023/07/why-priming-africa-s-smes-for-growth-isabout-more-than-money/
42 McKinsey Global Institute (2023). Reimagining economic growth inAfrica. Accessible at: https://www.mckinsey.com/mgi/our-research/reimagining-economic-growth-in-africa-turning-diversity-into-opportunity
43 Pradhan Mantri Gramin Digital Saksharta Abhiyann, (n.d.), Overview.
Available at: https://www.pmgdisha.in/about-pmgdisha/
44 Allwork (2023). Indian Prime Minister Call for an Upskilling of
the Workforce in New Technologies. Available at: https://allwork.
space/2023/07/digest-indian-prime-minister-calls-for-an-upskillingof-the-workforce-in-new-technologies/
45 Technical Education and Skills Development Authority (2021). IT-BPM
Industry Skills Prioritization: Feedback Report 2021. https://tesda.gov.
ph/Uploads/File/LMIR/2021/IT%20BPM%20Consultation%20Report.pdf
46 Technical Education and Skills Development Authority (2021). IT-BPM
Industry Skills Prioritization: Feedback Report 2021. https://tesda.gov.
ph/Uploads/File/LMIR/2021/IT%20BPM%20Consultation%20Report.pdf
47 White House (2023). Fact Sheet: Biden-Harris Administration Secures
Voluntary Commitments from Leading Artificial Intelligence Companies to Manage the Risks Posed by AI. Available at: https://www.
whitehouse.gov/briefing-room/statements-releases/2023/07/21/
fact-sheet-biden-harris-administration-secures-voluntary-commitments-from-leading-artificial-intelligence-companies-to-manage-the-risks-posed-by-ai/

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AI in Africa: A working paper - 21

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