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How is artificial intelligence (AI) used on the African
continent and what are the specific demands of African countries? We survey
different countries in Africa and look at their AI needs and challenges.
Governments across the world are prioritizing AI as the
basis for national competitiveness and African countries are no different. A
rapidly growing number of programmes, strategies, and pilot projects are being
launched across the continent. As a result, public policy is being shaped to
address gaps in infrastructure and specialist skills that might limit these
countries’ ability to compete globally.
There are notable differences in the levels of economic
maturity, compute and internet capacity as well as institutional frameworks in
each country of this vast continent, but at the same time most of them share
the same concerns.
One of the main ones is a common belief that in order to be
independent of technologies trained elsewhere and or owned by third parties,
each state should ideally develop its own sovereign AI systems. These should be
engineered to reflect linguistic diversity, address the
requirements of informal economies as well as resource‑strained public
services.
A May 2026 study by PwC found that an overwhelming
majority of African organizations are already engaging with AI but also that
few had succeeded in building out the technology “in ways that generate
sustained growth, operational reinvention or competitive advantage.”
As AI rises up on the agenda, countries that invest in
inclusive strategies, automation, innovation, and broad AI education - backed
by serious funding and robust national policies - will be positioned to lead.
This article snapshots a selection of African countries and
their pathways to engaging with AI.
Kenya: from maternal chatbots to helping farmers
The Kenya AI Strategy 2025–2030 aims to establish
a strong digital infrastructure for AI. It outlines priority AI applications
envisioning, for instance, a maternal health chatbot conversant in local
dialects, AI-driven teaching systems and translating agriculture data into “farmer-friendly
audio formats in local languages.” However, as the strategy document makes
clear, current infrastructure limitations “could slow down AI adoption and
limit the scalability of AI driven solutions across the country.”
It also acknowledges that Kenya’s current regulatory
environment for AI is “fragmented”, causing “inconsistencies and
inefficiencies” in AI governance, in turn, “making it challenging to
create a cohesive strategy for AI development and deployment.”
“Like many countries, the government was initially slow to
act on AI governance,” says Monica Okoth, Assistant Manager in the
Electrotechnical & ICT Division at the Kenya Bureau of Standards (KEBS).
“Policy makers didn’t fully understand the technology, so there were no
policies for a long time.” She says it was the private sector which led the
government to draw up an AI strategy and that KEBS was brought into the process
largely through private sector engagement.
Data ownership is a challenge
In particular, there are concerns about data ownership. Big
tech companies have previously collected indigenous knowledge or language data
without full disclosure, in addition to plundering the continent’s resources
for their requirements. (so-called techno-colonialism). “For example,
there was a case where biometric data was collected from communities without
proper government knowledge or transparency. The issue isn’t the data
collection itself since we need more data to reduce bias,” Okoth says, “but
ensuring full disclosure, consent, and clarity on how the data will be used.
Another concern is whether AI can take into account the
diversity of African populations. “Kenya has 42 languages, so developing models
for all of them would require huge investment,” she adds. “Because English and
Swahili are widely spoken, some therefore argue that we don’t urgently need
large language models (LLMs) in every indigenous language.”
Digital safety, privacy and security were part of a more
than USD 1 billion investment led by Microsoft and an Emirati AI
company to build and run a data centre for East Africa in Kenya’s Rift Valley.
The project promised to operate a “trusted data zone” under which local data
would be stored and governed by local laws.
However, since being announced in 2024, the project has yet
to kick off, with reports of development being tied up in red tape
and concerns about how much electricity from the grid is needed to run it.
Role of KEBS and standards
Recognizing the importance of international standards, KEBS
joined as a participating member of ISO/IEC JTC 1/SC 42:
Artificial Intelligence, in 2020. “We pushed for standards to be embedded in
Kenya’s national AI strategy, because without them, implementation would be
weak,” Okoth explains. “One of the government pillars now includes developing
standards for conformity assessment and responsible AI.”
KEBS has already adopted several international standards and
is developing local ones. For example, Kenyan Standard KS 2007:2025, a
Code of Practice for AI, outlines non‑functional requirements and includes a
full clause on trustworthy AI. It assigns responsibilities across the data
providers, developers, software managers, and end users.
“Implementation is challenging if standards aren’t enforced
or understood, so we also focus on conformity assessment. With donor support
(such as funding from the UK government) we’re developing AI and AI‑data
maturity models. These help organizations, especially start-ups and government
agencies, self‑assess their readiness for responsible AI adoption or
development. We’re also creating playbooks to guide them,” Okoth says.
Nigeria: building AI based on wide variety of languages
With over 500 languages, Nigeria is one of the most
linguistically diverse countries in the world. A LLM currently in development
aims to capture and build on this resource. N-ATLAS, short for Nigeria’s
African Tongue Language AI System, is designed to handle multiple languages
native to Nigeria, including Yoruba, Hausa, Igbo, and Nigerian-accented
English.
Launched last September, the centrepiece of Nigeria’s
National Artificial Intelligence Strategy (NAIS), it is a public-private
initiative led by the National Information Technology Development Agency
(NITDA), the National Centre for AI and Robotics (NCAIR) and local AI firm
Awarri.
“N-ATLAS is designed to understand and generate Nigeria’s
diverse voices, ensuring that the country’s linguistic richness is preserved
and reflected in the global Artificial Intelligence (AI) ecosystem,” the
Federal Ministry of Communications, Innovation & Digital Economy says.
For instance, farmers could use voice-based queries in Hausa
to access weather forecasts or market advice. Igbo-speaking students might
interact with AI tutors in their native tongue, improving learning outcomes in
areas with low literacy rates. Or the LLM could be tuned to customer service
where people’s queries “might differ significantly due to cultural and
linguistic factors.”
The NAIS acknowledges existing structural challenges in the
way of achieving its vision to make Nigeria a global leader in ethical and
inclusive AI innovation. To upgrade its data centre and edge computing
infrastructure, there are plans to offer tax breaks to investors. To build up
its software capacity, organizations like Data Science Nigeria (DSN)
offer upskilling and mentorship programmes. The Nigeria AI Scaling Hub is
a research incubator focused on AI solutions in health, education, and
agriculture, funded by the Gates Foundation. Additionally, the national
curriculum for basic and secondary schools has been revamped to incorporate
learning about AI, robotics, and cyber security. As DSN put it, “Africa cannot
negotiate its place in an AI-driven world without the technical workforce
required to hold that position.”
South Africa is leading the way
By most measures, South Africa is the continent’s leading
country when it comes to digital and AI development. One report ranks
South Africa as the only African country exceeding the global average of
working age adults using AI tools. Another identifies more than 725
AI start-ups in the country at the end of last year, significantly more than
the next best on the continent (Nigeria with 456).
Its National AI Policy Framework, released in 2024,
placed “a strong emphasis on a human-centred approach in AI systems”,
stipulating that applications should augment rather than replace human
decision-making. And yet plans to cement this as national policy had to be put
on hold earlier this year after it was revealed that some of the rules in the
draft were AI-generated. At least six of the document’s 67 academic
citations were found not to exist, suggesting that the draft did not in fact
have sufficient human oversight.
“We need to make sure we have all the right voices at the
table: people deeply immersed in AI, but also people in policy, law, and other
areas,” explains Professor Benjamin Rosman, Director, Machine Intelligence
& Neural Discovery, [JF1] at Wits University told CNBC
Africa.
He is tasked with leading an advisory panel to the
government to develop a new national AI policy. In his interview to CNBC
Africa, he stressed that people working in the field were already seeking to
bring in different perspectives to their work. Designing something
“future-proof” should stand them in good stead, he explained.
Much of the investment in South Africa’s data centre and
cloud infrastructure has come from overseas. Notably from Microsoft, which
recently pledged a USD 329 million expansion in cloud
infrastructure and AI training for Africa’s youngsters (a cumulative
USD 1,4bn investment in recent years). Google and Amazon also
all operate major platforms in Johannesburg and Cape Town.
These moves by overseas tech companies are viewed with a
degree of suspicion by several south African pundits involved in the field.
Rosman, for instance, queried whether South Africa should be happy relying on
US technology and that subscription fees for it are leaving the country. “The
country needs to build its own critical mass, widen participation, and ensure
it is aligned with global best practices around AI, and plot a way forward,” he
advised.
Egypt is an early adopter
The aim of Egypt’s National AI Strategy (2025-2030)
is to have AI contribute as much as 7,7% of total GDP by the end of the decade.
Achieving this would require training 30 000 specialists, supporting 250
startups, and expanding use of AI tools to over 35% of the total population (40
million people).
Egypt was an early mover on the continent, having issued an
early AI framework for growth in 2021. The second edition is “much more
ambitious” with a significant shift from solely using foreign technology to
creating a sovereign AI ecosystem.
Core to that goal is development of Egypt’s first nationally
built and owned LLM, called Karnak, which was announced at the AI
Everything MEA summit in Cairo last February. Karnak is intended
to “preserve linguistic and contextual relevance, especially for Arabic,” and
to underline Egypt’s push to become “a regional AI hub linking Africa, the
Levant, and the Gulf states.”
Applications powered by Karnak include a personalized
AI tutor supporting Egyptian history education in high schools, a
specialized translation tool and a suite of natural language processing engines
for colloquial Arabic.
Both editions of the AI strategy put ethical and responsible
use of the technology at its core. As established in the Egyptian
Charter for Responsible AI, the state is adapting international standards
like UNESCO’s Recommendation on the Ethics of AI and ISO/IEC 42001, the
International Standard for AI management systems, to local contexts,
emphasizing human-centeredness, transparency, fairness, accountability, and
privacy.
The work of African standards organizations
Several initiatives have emerged recently to develop cross‑border
AI standards for Africa.
EAC (East African
Community) recently called for
the responsible development of AI and stronger regional collaboration to drive
inclusive growth and innovation. AFSEC (African
Electrotechnical Standardization Commission) is creating a new technical
committee on AI, including AI-enabled products and services, with specific
consideration of African regional requirements, conditions, and priorities. It
will be launched next month at its 10th General Assembly.
ARSO (African
Regional Organization for Standardization): established a technical committee
on information technology with a proposal for a subcommittee to deal with
emerging technologies such as AI and IOT in May of this year.
“The goal is to create Africa‑centric AI standards,”
explains Okoth. “It doesn’t make sense for each country to reinvent the wheel
when resources are limited. Many African countries share similar cultural and
economic contexts, so pooling resources to develop continental standards is
more efficient and impactful.”
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