Africa Has an AI Strategy. The Hard Part Is Making It Matter

Artificial intelligence is becoming a policy issue in Africa faster than many governments are prepared for.

Across the continent, governments are developing national AI strategies, regulators are beginning to consider new rules, and companies are increasingly using AI in areas ranging from financial services to healthcare and education. The African Union has also adopted a Continental Artificial Intelligence Strategy that calls for an Africa-centred approach to the development and governance of AI.

On paper, this looks like progress.

But having an AI strategy is not the same thing as having the ability to shape what AI does.

That distinction matters.

Africa has spent years being treated primarily as a market for technologies developed elsewhere. The concern now is that the same pattern could repeat itself with AI: technologies are developed outside the continent, trained largely on data and assumptions that may not reflect African realities, and then introduced into African societies while governments try to regulate the consequences after the fact.

The question, therefore, is no longer whether Africa needs AI policy.

It is whether African countries can build enough capacity to make that policy meaningful.

A strategy is only the beginning

The African Union’s Continental AI Strategy is an important step. It recognises AI as a strategic issue for the continent and calls for responsible, inclusive and development-focused approaches. It also identifies infrastructure, data, skills, research, innovation and governance as important foundations for Africa’s AI future.

In May 2025, an AU high-level policy dialogue went further, calling on African countries to develop national AI strategies, policies, laws and regulations that reflect both the continental framework and their own national circumstances. The same dialogue called for stronger African participation in global AI governance.

This is the right direction.

But implementation is where the difficult questions begin.

A government can publish a strategy without having enough people who understand the technology well enough to regulate it. A parliament can pass legislation without having the technical capacity to scrutinise complex AI systems. A regulator can demand transparency from a technology company without necessarily having the tools or expertise to determine whether the information provided is meaningful.

That creates a dangerous imbalance.

The companies building increasingly powerful AI systems may have teams of engineers, lawyers, researchers and policy specialists working on a single regulatory question. A public institution in an African country may have a handful of officials responsible for an entire area of digital policy.

The problem is not simply a lack of regulation.

It is a lack of negotiating power.

Africa cannot regulate what it cannot examine

AI regulation depends on more than legal language.

Regulators need access to expertise, data, computing resources and independent research. They need to understand how automated systems are trained, how they perform, where they fail and who is affected when they fail.

This becomes particularly important when AI is introduced into public services.

Consider a government using an automated system to help determine who receives social assistance, a financial institution using AI to assess creditworthiness, or a public authority deploying facial recognition technology.

A regulation might say that such systems should be fair and transparent.

But what happens when an affected person asks why an automated system rejected their application?

Who checks the model?

Who has access to the data?

Who determines whether the system works equally well for different populations?

And perhaps most importantly, who has the authority to stop the system if it is causing harm?

These are not abstract questions. They are questions about power.

The data problem is also a governance problem

Africa’s position in the global AI economy is complicated by the continent’s limited access to some of the resources required to develop advanced AI systems.

The African Union itself has identified the shortage of high-quality datasets, computing capacity and AI talent as part of the continent’s AI divide.

This matters because data is not simply an input into AI.

It determines what systems learn about the world.

If African languages, communities, institutions and social realities are poorly represented in datasets, AI systems can perform badly when they encounter them. A system can appear highly capable in demonstrations while still failing people whose experiences are not adequately represented in the data used to develop it.

There is also a question of who controls African data.

African governments and institutions need to think carefully about what happens when valuable datasets leave the continent, who is permitted to use them, and whether African researchers and businesses can benefit from the resulting technologies.

Data governance should therefore not be treated as a technical issue that can be left entirely to data-protection specialists.

It is an economic and political issue.

Regulation should not become another imported template

There is a temptation in technology policy to look at what the European Union, United States or other major technology powers are doing and simply copy their approaches.

There is value in learning from these jurisdictions. African policymakers should study regulatory developments around the world and understand what has worked and what has failed.

But copying legislation is not the same as building policy.

Africa’s technology environment is different.

The continent contains countries with very different levels of digital infrastructure, institutional capacity, internet access, economic development and regulatory maturity. Even within individual countries, the realities of an urban technology hub can be completely different from those of a rural community.

A regulatory framework designed for a highly connected economy may not work in exactly the same way in a country where millions of people still face basic barriers to reliable connectivity.

African policymakers therefore need to ask a different question:

What does responsible AI governance look like in African societies?

Not what does it look like somewhere else?

The people affected by AI need a seat at the table

There is another part of the conversation that deserves more attention.

AI policy cannot be left exclusively to governments, technology companies and international organisations.

Researchers, journalists, civil society organisations, workers, students and ordinary citizens also need to participate.

This is particularly important because many AI decisions will eventually affect people who have never participated in a conversation about AI policy.

A worker whose job changes because of automation may never have attended a technology conference.

A farmer affected by an AI-powered agricultural system may never have heard of algorithmic accountability.

A young person whose application for a service is rejected by an automated system may not know that an algorithm was involved.

Policy that is designed without these people in the room risks becoming disconnected from the problems it is supposed to solve.

The African Union’s own work on AI has recognised the need for multi-stakeholder participation and broader consultation. Its consultations during the development of the continental strategy brought together different stakeholders to discuss AI opportunities, risks, capabilities and international cooperation.

That approach should continue beyond the development of a strategy.

Participation cannot end when the document is published.

Africa should be a rule-maker, not just a rule-taker

There is a bigger issue underneath all of this.

The countries that have the greatest influence over AI governance today are not necessarily the countries that will experience every consequence of the technology.

If decisions about AI standards, safety, data, intellectual property and international cooperation are made primarily by a small group of powerful governments and companies, other countries may eventually be forced to adapt to rules they had little influence over creating.

Africa should not accept that position.

The continent already has a collective framework through the African Union. In 2025, African leaders and policymakers explicitly called for a more representative global AI governance landscape and stronger African participation in international AI discussions.

But having a seat at an international meeting is not enough.

Influence comes from expertise.

It comes from research institutions capable of producing evidence that policymakers cannot ignore. It comes from regulators who understand the technologies they oversee. It comes from journalists who can investigate the effects of AI on ordinary people. It comes from local companies developing systems that understand African markets rather than simply adapting imported products.

And it comes from governments that are willing to invest in these capabilities for the long term.

The opportunity is bigger than regulation

The conversation about AI in Africa is often framed around what could go wrong.

That is understandable. There are legitimate concerns about surveillance, discrimination, misinformation, employment and privacy.

But Africa should not approach AI policy only as an exercise in preventing harm.

There is an opportunity to build something more ambitious.

African governments can use AI policy to encourage local research and innovation. Universities can develop expertise in African languages and datasets. Regulators can create clearer rules that give responsible businesses room to innovate. Governments can use procurement to support local technology companies instead of automatically turning to foreign providers.

The AU has already identified domestic AI capacity, African-led research, homegrown solutions and investment in infrastructure and skills as important priorities.

The challenge is turning those priorities into institutions and investments that survive beyond policy documents.

The next phase will determine whether Africa has a voice

Africa does not need another declaration that AI is important.

It needs the capacity to act on what it already knows.

The continent needs regulators who can challenge technology companies when necessary. It needs researchers who can generate African evidence. It needs journalists who can investigate how AI is being deployed. It needs civil society organisations capable of representing people who are often absent from technology debates.

And it needs policymakers willing to see AI governance as more than another item on a digital transformation agenda.

The African Union has given the continent a starting point. The real test will be whether member states can turn that common vision into national policies, institutions and investments that reflect their own societies while strengthening Africa’s collective position internationally.

The future of AI will not be determined only by the people who build the models.

It will also be determined by the people who decide where those models can be used, what protections must accompany them, who is accountable when they cause harm, and whose interests count when the rules are written.

Africa should not wait until those decisions have already been made.

It should help make them.