Over the past decade, Africa’s digital economy has evolved into what analysts describe as a “quiet but globally significant” transformation, defined by locally engineered solutions to deep-rooted challenges in financial services, healthcare delivery and commercial activity.
Gori Yahaya, the founder and chief executive officer of UpSkill Digital, a digital training and transformation consultancy, in this interview with Business A.M.’s Onome Amuge, speaks on these among others, noting that Africa’s defining digital advantage lies in its “context-first innovation culture,” where products are built around real-world constraints such as informality, limited banking access and infrastructure gaps rather than replications from developed markets. Excerpts:
Africa has made significant progress in mobile connectivity and digital financial inclusion over the past decade. How would you describe the continent’s digital evolution so far?
I would describe it as quiet, determined, and far more globally significant than the world has given it credit for. Certainly underestimated for a long time. But what is changing now is that what is being built on this continent is becoming genuinely unmissable, and the rest of the world is starting to pay attention in a way it should have much earlier.
Over the past few years there have been some genuinely game-changing inventions that came from right here. Ubenwa, founded in Nigeria in 2002, detecting birth asphyxia from a baby’s cry, Aerobotics in South Africa, and if we take it way back, there’s M-Pesa.
M-Pesa is worth pausing on because of what it actually represents. It wasn’t a technology company deciding to disrupt financial services for the sake of it. It was a solution built around a real and immediate local need: how do people move money when they do not have a bank account, work in the informal economy, and live hours from the nearest branch? That question was answered locally, and the answer went on to create hundreds of thousands of jobs, open up entirely new business categories and give millions of people their first meaningful relationship with the financial system.
That spirit of solving for the actual context rather than importing a solution designed for someone else’s market is what makes Africa’s digital story so distinctive. It is also that foundation that makes the AI moment feel like a genuine opportunity rather than another wave the continent watches from the shore.
In your opinion, what are the biggest misconceptions African businesses and professionals still have about artificial intelligence?
I hear this directly from business owners in our AI programmes across Nigeria, Mozambique, Kenya, and many other countries across the continent. The initial challenge we faced consistently was: ‘I am not a techie. How do I even get hands-on with AI?’ which is completely understandable, because the hype and the scale of opportunity being discussed can make it feel a little unreachable at times.
There is now a bigger shift towards a second version of that concern: ‘It is moving so fast, how can I even keep up?’ As AI capabilities roughly double every six to eight months, the realistic picture is that there is a growing gap between the people who have started and those who are still watching from the sidelines, curious but nervous about where it is all heading.
The second misconception is that AI is something you adopt once your business is big enough to justify it. The reality tends to be the opposite. For an SME owner managing everything from operations to customer service to accounts with a small team, the productivity gains from AI tools can be more immediate and meaningful than for a large corporation with specialist departments already in place.
Both misconceptions share the same root: people have absorbed a version of AI that was not designed with them in mind, or they have struggled to find a way in. Changing that starts with giving people hands-on access in environments where the examples, the language and the scenarios genuinely reflect their daily reality.
Do you think African companies risk falling behind globally if AI adoption remains concentrated among large corporations and multinational firms?
The risk is real, but I would frame the challenge slightly differently to how it is usually posed. The concern is not simply that large corporations will pull ahead of smaller businesses. The deeper problem is that AI capability risks becoming concentrated in a narrow layer of any organisation, large or small, leaving the majority of the workforce on the outside of a technology that is reshaping how work gets done.
I have seen multinationals in Lagos and Nairobi invest meaningfully in AI tools and infrastructure, only to discover that the people meant to be using them day to day were never brought along. The tools sat largely unused because the workforce capability was not there. The ROI evaporated.
For African businesses specifically, the stakes are higher because the SME and informal sector drives the overwhelming majority of employment across Nigeria, Ethiopia, Ghana, Tanzania and beyond. If AI capability stays locked inside the boardrooms of multinational firms, the broader economy misses the productivity gains that could genuinely shift things at scale. The question is not just who adopts first. It is how widely and how deeply the capability spreads.
Which sectors in Africa do you believe stand to benefit the most immediately from AI-driven productivity tools?
Financial services and fintech are the natural starting point, and for very good reason. The mobile financial inclusion story that M-Pesa/M-Kopa began has already fundamentally changed how millions of people across East Africa manage money and run businesses. AI builds on that foundation in practical ways: fraud detection, alternative credit scoring for people without formal credit histories, and personalised financial guidance reaching people who have never had access to a financial adviser. The infrastructure for digital trust is already embedded in everyday life, which makes the next layer of AI adoption far less of a leap.
But the sector I am perhaps even more interested in is retail and informal commerce. The scale of trading activity happening through WhatsApp, through open markets and through informal distribution networks across Nigeria and the broader continent is extraordinary. AI tools that help with inventory management, pricing, customer communication and basic bookkeeping have the potential to formalise and accelerate that economy in ways that policy has never fully managed.
Agriculture and healthcare sit just behind those two, given the significant impact that better data, earlier diagnostics and more accurate planning can have on communities that have historically been the most underserved.
How can small businesses and startups leverage AI without requiring massive capital investment or highly specialised technical teams?
The encouraging reality is that the most immediately useful AI tools for small businesses require neither significant capital nor technical expertise. Tools like NotebookLM, for tailoring your learning, Kling AI for creating video content, and Copilot, features are either free or very low cost, and they address the areas where SMEs consistently have the biggest gaps: creating marketing content, communicating with customers, researching new markets, and planning operations without needing a specialist for each.
The gap I see most consistently across West and East Africa is not a lack of awareness of these tools. Business owners know they exist. Many have opened one at least once. The gap is the absence of structured, practical time with someone who can show them how to connect the tool directly to the challenges they face in their business every day.
When that connection is made, even in a single two-hour UpSkill Universe AI session, the gains are immediate. A fabric trader who uses AI to write her first supplier email in English. A restaurant owner who generates a month of social media content in an afternoon. These are not future possibilities.
They are things we see regularly in our sessions, and they are available to any small business that gets the right kind of hands-on introduction.
There are concerns globally about AI replacing jobs. In Africa’s context, do you see AI as more of a threat to employment or an opportunity for workforce expansion and productivity?
The honest answer is that it is both, and anyone who tells you otherwise is not engaging seriously with the question. AI will come for a significant portion of the tasks that make up many people’s working day. That is already happening in customer service, data entry, basic content production and administrative processing.
But there is a critical distinction between tasks and jobs. Most roles are a collection of tasks, and AI is going to handle more of those tasks over time. What that opens up is space to spend more of your working day on the things that genuinely require human judgement, creativity, relationships and contextual understanding. Those are the things AI cannot replicate, and they are the things that make someone genuinely valuable.
For Africa specifically, I believe the opportunity considerably outweighs the threat, and the reason is the sheer scale of economic activity waiting to happen. The informal economy alone represents an enormous backlog of potential productivity. AI is one of the most powerful tools we have ever had for unlocking that potential. The critical condition is that the skills to use it are distributed widely and quickly enough to bring the majority of the workforce along.
That gap is what concerns me most, and it is where organisations need to take genuine responsibility. Building pathways for entry-level talent, creating structured routes for people to gain experience in an AI-augmented workplace, and not simply expecting the labour market to self-correct. This is a large part of why UpSkill Universe exists, and why the work we do with programmes like the Google Hustle Academy feels more urgent now than it ever has.
Do you think Africa risks becoming only a consumer of global AI technologies rather than a creator of AI-driven innovation? What specific capabilities should founders and business operators be prioritising today if they want to remain competitive in an AI-driven economy?
The risk of becoming primarily a consumer of AI technology built elsewhere is real, and I will not minimise it. The economics of AI development, which demand enormous compute infrastructure, vast training datasets and significant capital, do not currently favour the continent closing that particular gap quickly.
But I want to push back on the framing, because I think it sets up the wrong priority. The more urgent question is not whether Africa builds the models. It is whether Africa has enough people who can use them effectively, adapt them for local contexts, and build the products and services on top of them that the continent actually needs. That is an entirely achievable goal right now, without waiting for the infrastructure gaps to close.
The capabilities founders and business operators need to prioritise are practical rather than theoretical: prompt engineering, AI-tool fluency applied to specific business problems, and the ability to identify what to delegate to AI and what to retain as human judgement. That foundation is what everything else builds on, and building it does not require a computer science degree or a Silicon Valley budget.
UpSkill Universe recently partnered with Google Hustle Academy to expand AI skills training across Africa. What informed the decision behind this collaboration?
The collaboration came from a shared conviction that access to quality, practical AI skills training should not depend on how much money you have or what type of business you run. That might sound simple, but it is actually quite a specific design commitment, and not every programme in this space is built around it.
Google as a leader in AI, brings global reach, credibility and infrastructure. UpSkill Universe brings the on-the-ground facilitation expertise and the deep understanding of what needs to happen in a room in Lagos, Nairobi or Johannesburg for learning to genuinely land. That combination felt like a genuine fit rather than a convenient one.
What made the partnership feel right was the shared rejection of the content library model: creating a course, putting it online and calling the job done. The Hustle Academy is built around live, human-led sessions, practical application and community-driven learning. Those are not bells and whistles. In markets where the biggest barrier to AI adoption is confidence rather than awareness, the quality and format of the learning experience is not a secondary concern. It is the whole point.
The programme is now being opened beyond small business owners for the first time. Why was it important to expand participation at this stage? What practical AI skills will participants gain through the initiative, and how do those skills translate into real business or career outcomes?
The original Hustle Academy was designed specifically with SME owners in mind, because they are in many ways the most immediately affected by AI. They are responsible for every function of their business and typically have the least access to specialist support. That focus was right for where we started.
But what became very clear as we delivered across the continent is that the workforce challenge is far wider than business ownership alone. Employees, freelancers, job seekers and young professionals are all navigating a labour market that is changing rapidly, and they need the same quality of practical, expert-led training that we have been giving to business owners. Limiting access to one group when the need is this broad felt increasingly difficult to justify.
The skills participants gain are deliberately practical: how to use AI tools to research, plan and communicate; how to prompt effectively for specific work outcomes; and how to identify which parts of a daily workflow can be handed to AI and which genuinely need human judgement. The aim is for every participant to leave having already done something useful with AI, not just having been told that it matters.
Looking ahead five to 10 years, what would success look like for Africa in the AI era, and what must happen now for the continent to fully participate in that future?
Real success is not a headline number of AI-enabled startups or a strong position in a global readiness index, although those things matter. Real success looks like a young professional in Kano, a market trader in Mombasa and an operations manager in Johannesburg all having a genuine, working relationship with AI tools as a normal part of how they do their job. Not because they attended a workshop once, but because the education system prepared them for it, their employer expected it and accessible ongoing training was there when they needed it.
Getting there requires three things to happen at the same time. Governments need to treat AI literacy as workforce infrastructure rather than a digital add-on, with the same seriousness they give to roads and electricity. Large technology companies need to go well beyond content creation and invest in free, human-led practical training at genuine scale, with outcomes tied to employability and business growth. And employers across the continent need to start treating AI capability as a baseline expectation for the people they hire and invest in building it in the people they already have.
None of those things are impossible. The building blocks are already in place in several markets. But the pace needs to increase significantly in the next two to three years, because the window between where we are now and where AI reshapes the labour market is narrowing faster than most people realise.
The South African virus called Jacinta Ngobese-Zuma