Africa's Continental AI Strategy: Building an Inclusive and Responsible AI Future

An artificial intelligence system developed to support agricultural productivity may perform exceptionally well in one part of the world but struggle when deployed in Africa, where differences in crops, climatic conditions, farming practices and local languages can significantly affect its reliability. Similarly, an AI-powered public service platform may demonstrate impressive technical capabilities while remaining inaccessible to communities with limited internet connectivity or inadequate digital infrastructure.

These examples illustrate a fundamental challenge in the global development of artificial intelligence: technologies designed without sufficient consideration of African realities may fail to address the needs of the people they are intended to serve.

As artificial intelligence increasingly influences economic activity, public administration, education, healthcare and other essential sectors, African countries face the important task of ensuring that the continent is not merely a consumer of technologies developed elsewhere, but an active participant in shaping their development, deployment and governance.

It is against this background that the African Union's Executive Council endorsed the Continental Artificial Intelligence Strategy during its July 2024 session in Accra, Ghana.

The strategy establishes a shared continental vision for the responsible development and adoption of artificial intelligence, recognising both the opportunities the technology presents and the risks associated with its deployment. Central to this vision is the understanding that AI development in Africa should advance economic and social progress while respecting human rights, promoting inclusion and strengthening the continent's capacity to develop technologies suited to its particular circumstances.

For African governments, businesses, research institutions and technology developers, the strategy provides an important policy framework for considering how AI can contribute meaningfully to development while remaining accountable to the communities it affects.

AI applications that respond to local needs

One of the central themes of the Continental AI Strategy is the importance of directing artificial intelligence towards challenges that are relevant to Africa's development priorities.

The continent presents significant opportunities for AI adoption across sectors such as agriculture, healthcare, education, public service delivery and climate action. However, the potential value of these applications depends on their ability to respond effectively to actual needs rather than merely demonstrating technological sophistication.

In agriculture, for example, AI can potentially assist farmers in identifying crop diseases, interpreting weather patterns, improving resource allocation and accessing information that supports agricultural decision-making. These applications could be particularly valuable in rural communities where access to agricultural extension services and specialised technical expertise may be limited.

Nevertheless, the success of such systems depends heavily on the conditions in which they operate. An agricultural AI model trained primarily on data from Europe or North America may not accurately account for the crops, pests, soil conditions or climatic variations experienced in Kenya and other African countries.

Language accessibility presents another consideration. Where an AI application provides recommendations only in widely used international languages, farmers who primarily communicate in local languages may be excluded from its benefits.

Consequently, the development of agricultural AI solutions requires more than acquiring an existing model and introducing it into a new market. Developers must consider the relevance of the underlying data, the accessibility of the service, the availability of technical support and the procedures through which incorrect recommendations can be identified and addressed.

Similar considerations arise in public administration.

Across Africa, governments are exploring digital technologies to improve service delivery, reduce administrative delays and make public institutions more responsive to citizens. AI offers opportunities to support these objectives through applications such as automated information services, document processing and administrative decision support.

However, an AI system that accelerates the processing of public applications while incorrectly classifying certain applicants may introduce new forms of unfairness or exclusion. Where affected individuals have limited digital literacy, unreliable connectivity or inadequate access to complaint mechanisms, correcting those errors can become particularly difficult.

The relevant question is therefore not simply whether AI can make a service faster or less expensive, but whether its deployment improves the quality, accessibility and fairness of the service.

This requires meaningful consideration of the communities affected by the technology throughout its development and implementation. Accessibility, human oversight, error correction and mechanisms for challenging adverse outcomes should form part of the system's design rather than being introduced only after problems emerge.

The Continental AI Strategy provides a basis for approaching AI innovation in this manner, with technological development guided by identifiable social and economic needs.

Risk management and human rights

Although artificial intelligence presents substantial opportunities for African development, its adoption also introduces risks that require deliberate governance.

The Continental AI Strategy recognises the importance of human dignity, equality, inclusion and the protection of fundamental rights in the development and use of AI systems. These considerations are particularly relevant where automated technologies influence decisions affecting individuals' access to services, employment, education or other important opportunities.

AI systems can reproduce or amplify discrimination where their training data, underlying assumptions or design processes fail to reflect the diversity of the populations they serve.

For example, a system trained on information that inadequately represents particular communities may produce less accurate outcomes for those groups. Similarly, AI-enabled identification and monitoring technologies may create significant privacy and surveillance concerns, especially where safeguards governing their use are insufficient.

Generative AI also introduces challenges relating to information integrity. The ability to produce convincing text, images and other forms of content at scale can be exploited to disseminate misleading information, impersonate individuals or manipulate public discourse.

These risks cannot be addressed effectively through a uniform approach that treats every AI application as presenting the same level of concern.

A learning assistant used to support classroom instruction raises different legal and ethical questions from a biometric identification platform or an automated system used to determine eligibility for public benefits.

Effective governance therefore requires an assessment of the particular technology, its intended purpose, the context in which it will operate and the potential consequences of errors or misuse.

The degree of human oversight, transparency, accountability and opportunities for redress should be proportionate to the risks associated with the application.

For Kenya, the continental strategy should be understood alongside the country's existing legal and regulatory framework.

While the African Union's strategy provides important policy direction, its endorsement does not, by itself, establish a directly enforceable Kenyan AI statute. Organisations deploying AI must continue to identify and comply with the binding legal obligations applicable to their activities.

These may include requirements under the Constitution of Kenya, the Data Protection Act, 2019, and other relevant laws governing privacy, equality, consumer protection, employment and administrative decision-making.

Where AI systems process personal data, for example, organisations must consider the applicable data-protection principles, the lawful basis for processing, security requirements and the rights of affected individuals.

Similarly, where automated tools are incorporated into public-sector decision-making, their use must be evaluated against the legal obligations governing the exercise of public power and the protection of individual rights.

The strategy's emphasis on responsible AI therefore provides an opportunity for Kenyan institutions to strengthen governance practices while recognising that policy aspirations and binding legal requirements must be distinguished.

Infrastructure, data and skills

Africa's ability to participate meaningfully in the AI economy depends not only on the availability of advanced technologies but also on the infrastructure, data resources and human expertise necessary to develop and use them effectively.

AI development can require substantial computing capacity, reliable connectivity, suitable datasets and professionals with the technical skills to design, evaluate and maintain complex systems.

Access to these resources remains uneven across the continent. Without deliberate investment, the benefits of AI adoption risk becoming concentrated among a relatively small number of well-resourced institutions, businesses and urban communities.

The Continental AI Strategy recognises capacity-building as an essential component of Africa's AI development agenda.

Investment in digital infrastructure, research institutions and technical education can help strengthen the continent's ability to develop technologies that respond to local priorities. Such investment can also reduce excessive dependence on externally developed systems that may not adequately reflect African needs.

However, infrastructure alone is insufficient.

The quality and relevance of the data used to develop AI systems are equally important. In sectors such as agriculture, healthcare and education, locally representative datasets can improve the ability of AI applications to respond accurately to the circumstances in which they are deployed.

For example, medical AI systems developed using datasets that inadequately represent African populations may perform differently when applied in local healthcare settings. Similarly, language technologies trained predominantly on widely represented international languages may provide limited support for African languages and linguistic variations.

Developing more representative datasets can help address these limitations, but it also introduces legal and governance responsibilities.

The need for better training data does not eliminate obligations relating to privacy, confidentiality, intellectual property or the lawful collection and use of information.

For Kenyan organisations, initiatives involving the collection, sharing or reuse of personal data must be assessed against the Data Protection Act and applicable regulations. Where datasets contain commercially sensitive or proprietary information, appropriate contractual permissions and intellectual-property arrangements may also be necessary.

The development of AI capabilities must therefore proceed alongside the development of effective data-governance frameworks.

Capacity-building should also extend beyond technical professionals.

As AI becomes integrated into organisational processes, decision-makers in government, education, law, business and other sectors need sufficient understanding to assess proposed applications and recognise their limitations.

A procurement officer evaluating an AI-enabled public service platform, for example, should understand the questions that need to be asked about accuracy, data protection, technical support and accountability. Similarly, a lawyer advising on an AI procurement agreement should be capable of identifying the contractual and regulatory implications of the system's operation.

The objective is not to require every professional to become an AI engineer. Rather, it is to ensure that those responsible for adopting, supervising and governing these technologies possess the knowledge necessary to make informed decisions.

Meaningful AI capacity-building consequently requires technical expertise and institutional responsibility to develop together.

Cooperation and investment

The Continental AI Strategy also recognises that Africa's participation in the global AI economy will require sustained investment and cooperation among governments, research institutions, private companies and international partners.

Developing AI infrastructure, specialised expertise and locally relevant technologies can be resource-intensive. Regional cooperation provides opportunities to share knowledge, coordinate research efforts and avoid unnecessary duplication of investments.

African universities and research institutions have an important role in this process. Partnerships involving academic institutions, technology companies and public bodies can support the development of datasets, research programmes, technical expertise and practical applications addressing shared continental challenges.

For example, collaboration between agricultural researchers and AI developers could support the creation of crop-monitoring systems better suited to East African farming conditions. Similarly, partnerships involving language researchers and technology companies could advance the development of AI tools capable of serving communities that communicate in underrepresented African languages.

However, cooperation must be supported by clear legal and institutional arrangements.

Research partnerships and technology-development agreements frequently raise questions concerning ownership of intellectual property, access to datasets, permitted commercial uses and the allocation of responsibilities between participating organisations.

A Kenyan technology startup collaborating with a university to develop an AI application, for instance, should establish at the outset how newly created intellectual property will be owned, whether either party may commercialise the resulting technology and what restrictions apply to data contributed during the project.

Without such clarity, disagreements may arise when a successful research initiative progresses from experimentation to commercial deployment.

Similar considerations apply to collaborations involving public institutions, particularly where public resources, government-held information or externally funded research programmes are involved.

Funding arrangements also require careful consideration.

AI initiatives often attract support during their initial development or pilot phases, but long-term sustainability depends on continued maintenance, technical support, staff development and periodic evaluation.

A public service platform that performs successfully during a funded demonstration may become ineffective if the responsible institution lacks the financial or technical capacity to maintain it after the initial project ends.

Investment decisions should therefore consider the entire operational lifecycle of an AI application rather than focusing exclusively on development and deployment.

In this respect, the strategy's encouragement of cooperation and investment should be understood as a call to establish sustainable technological capabilities across the continent, rather than merely facilitating the acquisition of AI products.

Turning the strategy into national action

The ultimate significance of the Continental AI Strategy will depend on how effectively its objectives are translated into national policies, institutional arrangements and practical programmes.

African countries differ considerably in their digital infrastructure, regulatory frameworks, institutional capacities and economic priorities. Consequently, implementation cannot rely on a single model applied uniformly across the continent.

Each country must assess its existing capabilities, identify priority areas for AI adoption and determine the legal, financial and institutional measures required to support responsible development.

For Kenya, the strategy provides an important continental reference point for ongoing national discussions concerning AI governance, digital transformation and the development of the country's technology ecosystem.

Kenya's National Artificial Intelligence Strategy 2025–2030 also provides a domestic policy framework through which national priorities can be considered in relation to the broader continental agenda.

The relationship between continental and national policy is particularly important because effective AI governance requires both regional coordination and implementation through institutions operating within their respective legal mandates.

National implementation efforts should identify the public bodies and other stakeholders responsible for delivering particular objectives, establish realistic funding arrangements and develop measurable indicators of progress.

However, implementation should not be assessed solely by counting the number of AI systems acquired, training workshops conducted or pilot projects launched.

Such measures may demonstrate activity without establishing whether the technology has produced meaningful improvements.

A more useful evaluation would consider whether an AI-enabled service has improved accessibility, reduced administrative delays, delivered reliable results and provided effective mechanisms for identifying and correcting errors.

For example, a Kenyan public institution considering an AI-powered information service could begin with a limited pilot using approved public information. This would allow the institution to evaluate the system's accuracy, accessibility and operational requirements before expanding its role.

Where a proposed system would influence decisions affecting individual rights or eligibility for public services, the institution would need to undertake a more comprehensive assessment of the applicable legal obligations, risks and safeguards.

Transparency can strengthen this process. Clearly communicating the objectives and limitations of pilot projects, inviting feedback from affected users and documenting the results of evaluations can help institutions make better-informed decisions about further deployment.

Regional cooperation can support these efforts through shared research, common technical approaches and the exchange of lessons from successful and unsuccessful projects.

At the same time, national regulatory bodies must continue to exercise their statutory responsibilities in accordance with domestic law.

The objective should be to create a governance environment in which continental policy direction, national regulatory requirements and institutional practices reinforce one another.

For Kenyan businesses, technology developers and public institutions, this means approaching AI projects with an appreciation of both the development opportunities identified by the Continental AI Strategy and the legal obligations arising under Kenya's domestic framework.

A proposed AI initiative should be evaluated not only for its commercial or technical potential, but also for its suitability to local conditions, treatment of personal and proprietary information, accountability arrangements and long-term sustainability.

Ultimately, the African Union's Continental AI Strategy represents an important step towards ensuring that Africa participates actively in shaping the future of artificial intelligence.

Its significance lies in recognising that responsible AI development must respond to the continent's particular social, economic and institutional circumstances while advancing innovation, inclusion and the protection of fundamental rights.

For African countries, the challenge is now to translate that vision into practical investments, effective governance mechanisms and technologies that deliver measurable benefits to their populations.

Africa's AI future should not be defined solely by its ability to adopt technologies developed elsewhere, but by its capacity to shape, develop and govern AI systems that reflect the continent's priorities, values and development needs.

Our technology-law practice advises businesses, public institutions and technology developers on AI governance, technology procurement, data protection and the legal arrangements supporting responsible innovation. Contact our firm to discuss the contractual, regulatory and governance considerations relevant to your proposed AI project or partnership.

Source

The African Union's Continental Artificial Intelligence Strategy, endorsed by the AU Executive Council in July 2024, provides the principal policy framework discussed in this article. It outlines a continental approach to AI development and governance, with emphasis on responsible innovation, inclusion, capacity-building, investment and cooperation.