Scroll through any Ugandan university WhatsApp group today and you will find it: students using AI to draft essays, summarise lecture notes, write job applications, and debug code. Walk into any mid-sized company on Kampala Road and you will likely find someone quietly using ChatGPT to do in ten minutes what used to take an afternoon.
Dr. Lawrence Muganga, Vice Chancellor of Victoria University Kampala, has noticed. And he wants government to notice too — before the curve steepens.
“The number of people using AI in this country is growing rapidly,” he wrote this week. “Think about the work these tools are already doing. How many people would have to be hired to do the same tasks? Quite a lot.”
It is a simple observation with uncomfortable implications. In a country where youth unemployment remains one of the most stubborn policy challenges, and where a large share of formal jobs are built on the kind of repetitive, document-heavy tasks that AI handles easily, the question of readiness is not abstract — it is urgent.
Small scale today. Different picture in five years.
Dr. Muganga is careful not to overstate where Uganda is right now. AI adoption here is real but uneven — concentrated in urban centres, among the educated, and in sectors with reliable internet access. The vast majority of Ugandans are not yet interacting with these tools in any meaningful way.
But that is precisely the point.
“AI is already here, and people are using it, even if only on a relatively small scale,” he said. “Now imagine what the situation will look like in the next five years.”
The global trajectory offers a preview. In markets where AI has moved beyond early adoption, the disruption is not arriving slowly. It is arriving in waves — first at the edges of white-collar work, then deeper into the core. Customer service, paralegal work, data entry, basic financial analysis, content production: these are not distant casualties. They are already being restructured.
Uganda is not insulated from that. If anything, the compressed speed of technology adoption in developing markets — the same dynamic that saw East Africa skip landlines and go straight to mobile money — means the transition may arrive faster than policymakers are prepared to manage.
A direct challenge to government
Dr. Muganga’s remarks were not a prediction. They were a provocation — directed squarely at the state.
“What are we doing as a government to invest in such an important technology before it begins replacing jobs on a much larger scale?” he asked.
It is a question that cuts across several ministries at once. The Ministry of ICT and National Guidance, which has been developing Uganda’s national AI strategy. The Ministry of Education, where curriculum reform moves slowly. The Ministry of Finance, where technology investment competes against more immediate spending pressures. The Uganda Communications Commission, tasked with digital infrastructure but increasingly relevant to the AI readiness conversation.
The concern is not hypothetical. Countries that have moved early on AI workforce preparation — investing in digital skills curricula, creating regulatory frameworks, funding local AI research — are building a structural advantage that will be difficult to close later. Countries that wait risk inheriting the disruption without having built the adaptive capacity to manage it.
Yes, jobs will go. But that is only half the sentence.
Dr. Muganga does not make the error of treating AI as purely a threat.
“Whether we like it or not, AI will replace some jobs,” he wrote. “At the same time, it will create new opportunities.”
That dual reality matters. Across the continent, AI is already generating new categories of work: prompt engineers, AI trainers, automation consultants, digital product managers, data analysts fluent in machine learning tools. Uganda’s technology sector — small but growing — is positioned to compete for some of that work, particularly given the country’s young population and its universities’ expanding ICT programmes.
Makerere University’s College of Computing and Information Sciences has been at the forefront of that effort, producing graduates increasingly literate in data science and software engineering. Institutions like KIU and UCU have followed. The raw material is there.
But training graduates is not the same as preparing a workforce. The challenge is broader — reaching the working Ugandan already employed in a role that AI may partially or fully automate, giving them the tools to adapt, retrain, and move toward higher-value work rather than simply being displaced.
The real question
For Dr. Muganga, the stakes come down to one thing: agency.
“The real question is whether we are preparing our people to adapt and benefit from that change,” he said.
That framing matters. The debate around AI in Africa is too often cast as a binary — adopt it fully or fear it entirely. The Victoria University Vice Chancellor is arguing for a third position: informed, strategic preparation. Not panic. Not complacency. Investment in people before the inflection point arrives.
The tools, as he correctly notes, are already here. The policy window to get ahead of the transition is narrowing. Whether government will move while there is still time to shape the outcome — rather than simply manage the aftermath — is the question Uganda now needs to answer.
