The next phase of artificial intelligence (AI) will not be defined by chatbots answering questions. It will be defined by systems that can do the work.
AI agents can plan tasks, use digital tools, analyse information, interact with other systems and execute processes with limited human intervention. That changes the economic significance of AI. Instead of simply helping a worker write a report, an agent could handle parts of customer service, compliance, research, logistics or administration.
For Africa, the question is therefore becoming bigger than whether people are using ChatGPT. Who will capture the economic value created by agentic AI?
That matters because AI could become part of the machinery through which businesses and governments operate. A 2026 IMF analysis estimates that faster AI adoption could raise productivity in sub-Saharan Africa by as much as 2.1% over the next decade. But the same analysis points to electricity, connectivity, digital infrastructure, skills and institutional capacity as major constraints.
Uganda illustrates both sides of this opportunity. The country is developing a National AI and Emerging Technologies Strategy and has been working with UNESCO on its AI readiness. Local initiatives such as Sunbird AI’s work on multilingual models also demonstrate that Uganda can develop AI around local languages and realities rather than simply consume systems designed elsewhere.
But agentic AI raises the bar. An AI agent cannot transform agriculture simply because the technology exists. It needs reliable agricultural data, access to weather and market information, digital systems that can communicate with one another and enough connectivity to operate. The same applies to banking, healthcare, logistics and government.
This makes Uganda’s wider digital transformation just as important as its AI strategy.
Consider agriculture. An AI agent could potentially bring together weather, market and farm information to help farmers or agribusinesses make decisions. In banking, agents could support fraud detection, compliance and customer service. In government, they could process large volumes of information, identify inefficiencies and automate routine administrative work.
The potential value is not limited to creating technology jobs. It is about allowing organisations to produce more with the resources they already have.
For an economy where capital, specialised skills and institutional capacity are constrained, that productivity gain could be significant.
But there is a more strategic question. Who owns the intelligence? If African businesses and governments increasingly depend on AI agents built on foreign infrastructure, foreign models, foreign datasets and foreign platforms, adoption could improve productivity without fundamentally changing the continent’s position in the digital economy.
Africa could become a large market for AI while much of the value flows elsewhere.
That is why the African Union’s Continental AI Strategy places emphasis on African capacity, data, infrastructure and responsible governance. The objective is not simply to ensure that Africans use AI, but to build the capabilities needed to participate in and benefit from the AI economy.
For Uganda, this means AI readiness cannot be measured by the number of people using generative AI tools. It must also be measured by the quality of the country’s data, digital infrastructure, skills, institutions and ability to govern automated systems.
The country does not need to build the world’s biggest AI model. It needs to build the foundations that allow Ugandan companies, public institutions and innovators to deploy AI effectively while retaining influence over how it is used and where the value goes.
That is the real economic question behind agentic AI. The chatbot era taught Africa how to use AI. The agentic era will test whether Africa is ready to build, govern and capture value from it.
