A Journey of Digital Transformation and Social Impact
I’m Abisola Areola, a data and digital transformation strategist and the founder of Skills Co-op, a social enterprise focused on opening digital and AI-skills pathways for people the labor market often overlooks. My work bridges research and delivery: I have spent seven years leading digital and data programs across the United Kingdom and Nigeria, publishing research on how people make sense of technology, and building the tools that research argues for. If you want the shortest version of me, it is this: I care less about whether technology works and more about whether people are equipped to build alongside it.
The Path That Wasn’t a Dream
It wasn’t a childhood dream. It was a series of doors I kept pushing until one opened. I did not grow up saying I wanted to be in technology; I grew up watching how opportunity was handed to some people and withheld from others, and wanting to understand why.
The Accumulation of Experience
The journey was not a straight line; it was an accumulation. I started in project management, learning how large, complicated things actually get built and delivered. That pulled me into digital transformation, where I saw that the technology was rarely the hard part; the people and the change around it were. That, in turn, drew me to data because it was the thread running beneath all of it, the thing that could tell you whether any of the change was actually working.
Founding Skills Co-op is where everything came together. I did not switch careers four times. I simply kept following one question through four different rooms, and each room taught me something the next one needed.
The Power of Data and Analytics
What inspired me in data analytics and digital transformation happened in that order, and the order matters. I was a project manager first. Then I moved into digital transformation, and I kept running into the same wall: organizations would invest heavily in new technology and still fail to change, and nobody could tell me precisely why. The tools worked. The transformation didn’t.
Data was where I went looking for the answer. Once I could see the numbers, the pattern became obvious. Most organizations are rich in data and poor in action. They can watch a problem forming and still fail to act on it.
Analytics gave me the language to prove what transformation had only allowed me to suspect: the gap is rarely the technology. It is the human system around it that was never designed to absorb the change.
A Defining Moment in Nigeria
Leading a national telemedicine program in Nigeria was the moment everything crystallized for me. We built an app we believed could be a game changer, and when COVID hit, it became exactly what the country needed: a way to reach a doctor without leaving home. It would have been easy to stop there and call it a success.
But an app only serves people who own the right phone, and in Nigeria that is a much smaller group than most people assume. Although mobile coverage reaches more than 90% of the country, around 72% of Nigerian adults still do not own a smartphone, and roughly 130 million Nigerians remain offline altogether. The signal is there; the device is not.
So the decision I am proudest of was building an interactive voice service alongside the app, deployed across the major mobile networks, so that someone with the most basic phone could still reach a healthcare practitioner with a simple call. We understood the reality of our country: the people who most need healthcare are often the very people a smartphone-only service would quietly leave behind.
That taught me something I have never let go of: real transformation is measured at the edges, by whether it reaches the people technology usually leaves behind. A solution that works only for the already connected is not transformation; it is convenience for the comfortable. Everything I have built since, including Skills Co-op, carries that principle at its core.
Current Projects and Future Vision
We are building a platform designed to be AI-native from the ground up, rather than a traditional course with AI bolted onto it. It has a built-in AI system that supports learners directly as they work, adapting to how each person learns.
The philosophy is simple but important: people should not just be taught about AI; they should learn by building with it. I proved that to myself first. I built a consumer application end-to-end using AI, without writing a single line of code, as a non-technical founder. If I can do that, it can be taught, and teaching it is exactly what the platform is for.
Research and Human-Centered Insights
My research interests are driven by the sociologist in me. I have always believed that research is one of the truest ways to understand society, to see not just what people do, but why they do it and what they are really afraid of.
My work has explored how patients build or withhold trust in technology-mediated healthcare, and how communities develop their own moral language in digital spaces. On the surface, those are different studies. Underneath, they are the same question: how do human beings make sense of systems that are changing faster than they can process?
Challenges and Lessons Learned
The hardest challenge was the very one Skills Co-op now exists to solve. The first door I ever had to force open was my own. Early in my career, I knew exactly what I wanted to do but could not find a way in because opportunities rarely go to people who simply show promise. I carried that memory into everything that came after.
Building a social enterprise brings its own challenges, and I will be honest about them. I have built this largely without secured funding, doing the work of an entire team as a solo founder, holding a long-term vision while managing the day-to-day operations, and pursuing grants and partnerships while still building the product itself. It is hard, and I would not pretend otherwise.
But here is what I have learned: building with AI has enabled me to do the work of many with the resources of one. The constraint became the proof. The very capability that helped me survive the challenge is now what I teach others.
Advice for Professionals Navigating AI
I understand the fear because it is really two fears wearing one coat: the fear of being replaced and the fear of not being smart enough to keep up. So let me speak to both.
You do not need to understand how AI works under the hood to work brilliantly with it, any more than you need to understand engine timing to be an excellent driver. What you need is to stop treating it as either magic or a threat and start treating it as a colleague: capable, fast, occasionally wrong, and much better when you direct it well.
I am a non-technical founder, and I built real software with AI by learning to ask, verify and iterate, not by learning to code.
Essential AI Skills for the Future
Four, and not one of them requires a computer science degree. I call them the difference between using AI and commanding it.
First, learn to prompt well: how to ask AI for what you actually need, with clarity and context. Second, learn to verify: how to check its work, because AI will confidently give you an answer even when it is wrong, and the person who cannot tell the difference is at risk.
Third, learn judgment: knowing when to trust AI and when to overrule it. And fourth, learn to build: using AI to create things, not just answer questions, because that is where the real leverage lies.
If you take nothing else from this, take this line and sit with it: the professionals who can direct, verify and build with AI will lead those who can only consume it. That shift is not coming; it is already here, and it is not waiting for anyone to feel ready.
