By DigiVibers Team
Uganda’s artificial intelligence (AI) ambitions are steadily gaining traction, but regulatory uncertainty, infrastructure gaps, and fragmented systems continue to slow progress, limiting innovation and the country’s broader digital transformation.
Speaking at the Uganda Deeptech Summit in Kampala, James Byaruhanga highlighted the persistent infrastructure constraints that are holding back AI development. While Uganda has made strides in connectivity—with internet penetration estimated at 68–70% and over 6,600 kilometres of national backbone supported by an additional 25,000 kilometres of private sector fibre—critical gaps remain.
“We still have very limited access to advanced computing and storage infrastructure, and the last-mile connectivity challenge remains significant, especially in rural areas,” Byaruhanga said.
He noted that although fibre-to-the-home services are expanding in urban areas, rural and peri-urban communities remain underserved, deepening the digital divide. Beyond connectivity, he highlighted systemic barriers including high lending rates, limited data centre capacity, and what he termed “GPU poverty”—a shortage of advanced computing hardware needed for AI.
“We still have very few neutral data centres to support ecosystem growth. Cloud, data centres, and AI are interdependent—if one layer is weak, the entire stack struggles,” he explained.
Byaruhanga also pointed to fragmented policy approaches between government and the private sector, warning that misalignment continues to slow innovation. “Regulators are often playing catch-up as technology evolves faster than policy frameworks,” he said, cautioning that Africa risks becoming a “data colony” without deliberate investment in local infrastructure.
From a regulatory and ecosystem perspective, Arthur Mukembo highlighted how fragmentation continues to affect startups.
“We tend to see a lot of caution in how startups engage with AI. There’s always that concern that by using a certain technology, you might run into trouble with regulators,” Mukembo said.
He acknowledged that regulators such as the Insurance Regulatory Authority and Capital Markets Authority are becoming more progressive through sandbox frameworks, but emphasized the need for a unified, multi-sector approach.
“The real opportunity lies in building a cohesive sandbox framework that allows innovators to test AI solutions across industries with clear guidance,” he said.
Mukembo also pointed to government’s dual role as both regulator and enabler, noting its vast data reserves across sectors like health and security. However, he stressed the need to structure access.
“The question is how to systematize access to this data—how to anonymize it, share it safely, and even monetize it sustainably,” he said.
While reforms such as challenge grants and co-creation partnerships are emerging, startups still face difficulties transitioning from pilot projects to scalable businesses—an issue that continues to limit commercialization.
At the policy level, Monica Musenero the minister for Science and Technology said government has made deliberate efforts to strengthen the science, technology and innovation ecosystem, but acknowledged persistent structural weaknesses.
A 2022 baseline assessment revealed low performance across key indicators, which she attributed to a “Black Box” challenge—limited understanding of how science translates into economic value.
In response, government introduced the STI Economic Highway, linking research to commercialization and driving investments in sectors such as mobility, pharmaceuticals, and agro-processing. Flagship projects including Kiira Motors, Dei BioPharma, and Uganda’s first satellite have created over 150,000 jobs and generated assets worth more than $1.5 billion.
However, funding for STI remains low at just 0.17 percent of GDP, far below the national target, underscoring the need for increased investment and coordination.
Beyond Uganda, experts say these challenges reflect a broader continental trend. Gilles Q. Hacheme noted that infrastructure gaps—particularly in connectivity, power, and computing—are slowing AI adoption across Africa.
“A data centre is not a standalone solution. It requires connectivity, power, and a supporting ecosystem,” he said, adding that financing such infrastructure remains a major hurdle.
Similarly, Dr Prince Abudu emphasized that Africa’s infrastructure remains fragmented, limiting its ability to fully utilize growing data resources.
“We now have more data, but the challenge is what to do with it without the right infrastructure,” he said.
As Africa pushes toward digital transformation and AI adoption, experts agree that stronger collaboration between governments, private sector players, and global partners will be essential. Without coordinated investment in infrastructure and regulatory alignment, Uganda—and the continent at large—risks remaining a consumer rather than a creator in the global AI economy.