Africa’s youthful population is often cited as a demographic advantage. But according to software developer Mukhtar Abdussalam, that advantage only counts if young innovators are given the data, funding, and platforms to build AI solutions rooted in African realities. He spoke with Guardian to discuss the intersection of artificial intelligence, accessibility, and public service.

Artificial intelligence has dominated global headlines this year. Beyond the headlines, what conversation do you think Africa should really be having about AI?

Africa should be talking less about AI as a trend and more about AI as infrastructure for solving real problems. The real question is not whether Africa should use AI, but what kind of AI we want, who it serves, who controls the data, and whether it improves ordinary people’s lives.

For me, the conversation should focus on practical impact, better public services, faster healthcare access, smarter education support, improved agriculture, safer financial systems, and more efficient government processes. Africa must not become only a consumer of imported AI tools. We should be building systems that understand our languages, our institutions, our informal economies, and our social realities.

Technology often promises inclusion, yet many citizens still struggle to access basic digital services. How do we bridge the gap between innovation and accessibility?
We bridge that gap by designing technology around people, not around systems. A digital service is not truly successful because it is online. It is successful when ordinary citizens can actually use it, including people with disabilities, people with low digital confidence, people using older mobile phones, and people in areas with poor internet access.

That means simple language, mobile-first design, accessible forms, low-bandwidth options, clear error messages, and alternative support routes for people who cannot complete the journey online. Innovation must not mean building something impressive that only a small group can use. Real innovation is when technology removes barriers rather than creating new ones.

You have worked across AI, automation and accessible web platforms. How do these three disciplines intersect in creating better public services?

They intersect around one goal: making services faster, fairer, and easier to use. AI can help identify patterns, support decision-making, and improve how information is delivered. Automation can remove repetitive manual tasks and reduce delays. Accessibility ensures that the service remains usable by everyone, not just technically confident users.
In public services, all three must work together. For example, if a process is automated but not accessible, some citizens will still be excluded. If AI is introduced without clear human oversight, trust can be damaged. If a website is accessible but the back-office process is slow, the citizen still experiences frustration. Better public services come from connecting the front end, the back end, and the human need behind the service.

Digital transformation is frequently described as a technology challenge, but isn’t it equally a leadership and culture challenge?

Absolutely. Technology is often the easier part. The harder part is leadership, culture, and willingness to change how things are done. Many organisations try to digitise an old process without asking whether the process itself should be redesigned.

Strong leadership is needed to create the right environment for digital transformation. Teams need permission to challenge outdated processes, collaborate across departments, test ideas, learn from users, and measure impact. A good digital culture is not just about buying new tools. It is about building trust, accountability, curiosity, and a shared understanding that technology should serve people.

What does “human-centred AI” actually mean in practice, particularly within African public institutions?

Human-centred AI means AI that starts with the citizen, not the technology. In practice, it means asking: What problem are we solving? Who might be harmed? Can the decision be explained? Is there a human appeal route? Is the data fair and representative? Does the system work for people in rural communities, people with disabilities, and people who speak local languages?

Within African public institutions, human-centred AI should never be about replacing public responsibility with algorithms. It should support better decisions, reduce delays, and improve access, while keeping human judgement, transparency, and accountability at the centre.

Do you think governments are asking the right questions about AI, or are they focusing too heavily on the technology instead of the problems it should solve?

I think many governments are still too focused on the technology itself. The question should not be, “How do we use AI?” The better question is, “Which public problems are causing the most pain, delay, cost, or exclusion, and can AI help us solve them responsibly?”

AI should not be treated as a magic solution. Before introducing AI, governments should understand their data quality, legal responsibilities, citizen needs, staff capacity, and ethical risks. Sometimes the best solution may be better data sharing, clearer forms, process automation, or improved service design. AI is powerful, but it works best when it is applied to a well-understood problem.

There is growing concern that AI systems may reinforce existing inequalities if they are trained on incomplete or biased data. How can African countries avoid repeating mistakes made elsewhere?

African countries can avoid this by being intentional from the beginning. We need local data, local testing, and local governance. AI systems should be tested across different languages, regions, genders, income levels, disabilities, and levels of digital access.

Governments and institutions should also demand transparency from vendors. If an AI system is being used in a public context, there should be clear information about what data it uses, how it makes recommendations, how it is audited, and how citizens can challenge outcomes. We should not import systems blindly and assume they will work fairly in African contexts. Fairness has to be designed, tested, and monitored.

Accessibility is often treated as an afterthought in digital projects. Why should it be considered from the very beginning?

Accessibility should be considered from the beginning because it affects the structure of the whole service. If it is added at the end, it usually becomes a patch rather than a principle. That leads to poor user experience, higher cost, and sometimes exclusion of the very people public services are meant to support.

Designing accessibly from the start improves the service for everyone. Clear language helps all users. Good contrast helps people using phones outdoors. Proper form labels help screen reader users and also reduce mistakes. Logical navigation helps people with disabilities and people who are not digitally confident. Accessibility is not a separate feature. It is a good service design.

One of Africa’s greatest strengths is its youthful population. How can young innovators help shape AI solutions that reflect local realities rather than imported assumptions?

Young African innovators are close to many of the problems AI should be solving. They understand the transport issues, payment behaviours, language mix, education gaps, healthcare access problems, and informal systems that do not always appear in imported technology models.

To unlock that potential, governments, universities, and private organisations need to give young people access to data, mentorship, funding, cloud tools, and real public-sector problems to solve. We also need procurement systems that allow smaller local innovators to participate. Africa’s youth should not only be trained to use AI tools. They should be supported to build AI solutions that carry African context, values, and creativity.

As AI becomes more sophisticated, public trust becomes increasingly important. What principles should guide responsible AI development in Africa?

Responsible AI in Africa should be guided by fairness, transparency, privacy, accountability, inclusion, and human oversight. People should know when AI is being used. Institutions should be able to explain how decisions are supported. Sensitive data should be protected. There should be clear responsibility when something goes wrong.

Most importantly, AI should not deepen exclusion. It should be tested with the people it is meant to serve, not only in boardrooms or labs. Public trust grows when citizens can see that technology is improving services without taking away their rights, dignity, or voice.

Looking ahead, what gives you the greatest optimism about Africa’s role in shaping the future of artificial intelligence, automation and inclusive digital innovation?

My greatest optimism comes from Africa’s young population, creativity, and ability to adapt quickly. Across the continent, young people are already using technology to solve problems in finance, education, healthcare, agriculture, logistics, and civic participation. That energy is a major advantage.

I am also optimistic because Africa has the opportunity to build differently. We do not have to repeat every mistake made elsewhere. We can design AI and automation with inclusion, accessibility, local languages, and public value from the start. If we combine technical talent with responsible leadership and a clear focus on real human problems, Africa can help shape a more inclusive future for artificial intelligence, not just participate in it.