By Folu Adebayo

This column is usually about boards, regulators, and the governance of artificial intelligence. But this week I want to write about a child.

My son’s name is Akintade. He is autistic. And the journey of getting him to a place where the world saw what I saw that took years longer than it should have.

I want to tell you what that journey was actually like. Because I think most discussions of AI in our newspapers are missing something important and Akintade is the reason I know it.

The years I do not talk about often

When Akintade was young, I knew. Not in any clinical way. I just knew. A mother knows.

I took him to GPs who told me to wait and see. I took him to schools who said he would catch up. I took him to family members who told me I was worrying too much. The system around him was full of patient, well-meaning people. None of them could see what I could see.

The wait for formal assessment in our NHS was years. Years during which he was in a classroom that did not understand him. Years during which I sat in meetings as a senior professional, carrying invisibly the knowledge that something was wrong with my child and the inability to prove it.
I want African mothers reading this to know I see you. Because what I went through in the United Kingdom, you may be going through with even fewer resources, even longer waits, even less understanding from the system around you.

The autism diagnosis journey is one of the loneliest journeys a parent can walk. And it is happening, right now, in Lagos and Abuja and Accra and Nairobi and Kano and Cape Town. To mothers and fathers who watch their children struggle and have no idea where to turn.

“The autism diagnosis journey is one of the loneliest journeys a parent can walk.”

The promise I made

Somewhere in the middle of our journey with Akintade, I made myself a promise.
If I ever got to a place where I could help if my skills and credentials and energy ever amounted to something useful. I would build something so that no parent had to walk that journey alone. Not in the United Kingdom. Not in Nigeria. Not anywhere.

For a long time the promise sat there. Akintade grew. He became the best of himself. He found his strengths. He became the brilliant, particular, wonderful young man he is.

And artificial intelligence developed.

What AI is actually for

This is where we usually pause in this column to talk about governance, risk, regulators, and the corporate implications of artificial intelligence.

Today I want to make a different point.
Artificial intelligence at its best, used carefully and responsibly has the capacity to do something the institutions around us have not always done. It can listen. It can help a parent put words to what they are seeing. It can produce a structured report at three in the morning when there is nobody else to talk to. It can do this in the parent’s own language. It can do this for free.

It cannot diagnose. It cannot replace the clinical professionals our children need.
But it can hand a worried, exhausted, isolated parent something tangible to walk into a GP appointment with.
That is the gap I have built into.

The tool that came from a promise

It is called Neurohelp.ai. The website is www.neurohelp.ai . It is free. It is available in ten languages including Yoruba. It works for any age from eighteen months to adulthood. It carries no advertising and asks nothing of the family using it.

I built it for the mother who knows. The father who is too tired to keep fighting alone. The grandmother holding the baby and wondering why he does not respond to his name. The teacher who suspects something but does not know how to raise it with the parent. The adult who has spent forty years wondering why they are different.

Last week a mother contacted me. She had been on a waiting list in UK for years. She had tried Neurohelp.ai. She had generated a report. She had taken it to her GP. She had finally, for the first time in years ,booked the appointment that might change her child’s life.

She sent me a message saying thank you. She told me she had cried while typing it. She said I deserved an MBE for what the tool had done for her family.
And I cried too.

Because for a moment, I felt the promise I made years ago land in the world.

“The value of AI is not measured in boardrooms. It is measured in a single mother finally having the words to describe her child.”

Why I am writing this in a business column

I am writing this in a column about AI because I want African business leaders, technologists, regulators, and entrepreneurs reading this newspaper to understand something.

Artificial intelligence is not just a tool for productivity. It is not just a competitive advantage. It is not just a regulatory headache.

It is one of the most important opportunities Africa has ever had to close the gaps that the institutions around us have not yet closed for children with autism, for mothers in rural areas, for adults navigating diagnoses, for communities historically underserved.

If you are building AI in Africa, build it for them. If you are funding AI in Africa, fund the founders building it for them. If you are governing AI in Africa, make space for the small, mission-driven tools that do not have venture funding but do have purpose.
Because the value of AI is not measured in the boardrooms of Silicon Valley or the regulatory texts of Brussels. It is measured in a single mother in Lagos finally having the words to describe her child’s experience. It is measured in a GP appointment booked. It is measured in a family no longer alone.

The work continues

Akintade is now a young man. He inspires me daily.

Neurohelp.ai is the tool I built because I love him. Akintade Autism Centre is the work I do because I want every family to feel the support that I have. The charity Autism Treatment Support Initiatives UK registered, is the structure that makes that work sustainable.

I share this not as a promotion. I share it because the journey from one family’s pain to a tool that can help thousands is exactly the kind of journey African AI can lead the world on.

If you know a family on a waiting list, share Neurohelp.ai with them today.

If you are a parent reading this who is carrying invisible weight at work and at home , I want you to know you are seen. You are not alone. And the work you are doing for your child matters more than almost anything else in this world.

The day I built Neurohelp.ai was the day I kept a promise I made to myself in the darkest part of our journey.

Africa’s AI moment can be a thousand kept promises. To a thousand families. In a thousand languages. Free of cost. Built with love.

That is what AI is actually for.

By Folu Adebayo

A lawyer in the United Kingdom needed to summarise a confidential client document. Forty pages. A busy day. So they did what millions of professionals around the world now do without a second thought.

They pasted it into an AI tool.

Faster than reading it line by line. Nobody had told them not to. Nobody had told them they could. There was no policy. No training.

No record of the decision.

It seemed harmless. It was not.

A UK tribunal has now ruled that uploading confidential documents to an AI tool can be treated as the equivalent of placing them in the public domain. The legal privilege protecting those documents, the confidentiality that is the very foundation of the relationship between a professional and their client was lost. Permanently.

Not because anyone acted in bad faith. Because the tool did what such tools do the moment information is entered into them.

“The employee was not trying to do anything wrong. They were trying to work faster.”

Why this matters far beyond the United Kingdom

It would be easy for African business leaders to read this as a distant story. A British tribunal. A British case. A British problem.

That would be a mistake.

The behaviour at the centre of this ruling a professional pasting confidential information into an AI tool to save time is happening in every law firm, every bank, every hospital, every government office, and every consultancy in Lagos, Nairobi, Accra, and Johannesburg right now. Today. As you read this.

The technology does not respect borders. The behaviour does not respect borders. The risk does not respect borders.

The only thing that varies from country to country is whether there is a governance framework in place to manage it and whether the people using these tools have been told, clearly, what is and is not permitted.

In most African organisations, that framework does not yet exist.

The quiet leak

Consider what is most likely happening inside your own organisation as you read this.

A member of staff has a long report to summarise. They paste it into a free AI tool.

A colleague is drafting a difficult email and asks an AI assistant to improve the wording including the confidential context. Someone in finance uploads a spreadsheet of sensitive figures to ask the AI to analyse it. A junior employee, eager and capable, uploads a client contract to extract the key terms quickly.

None of these people are acting maliciously. Every one of them is trying to do their job well.

And every one of them may be moving confidential information client data, commercial secrets, personal information, privileged material outside the protected boundary of the organisation.

This is not a hypothetical risk. Industry research suggests that the overwhelming majority of organisations have employees using AI tools, while only a small minority have any policy governing what may be entered into them. The gap between adoption and governance is not narrowing. It is widening.

“The technology does not respect borders. Neither does the risk.”

Why Africa is particularly exposed
There are three reasons this risk is especially acute across African markets.

First, AI adoption across Africa has been rapid, mobile-first, and largely informal. Professionals have embraced AI tools with energy and ingenuity often ahead of the organisations they work for. That is a strength. But it means usage is running far ahead of governance.

Second, many African organisations do not yet have the data protection infrastructure, the internal compliance functions, or the governance frameworks that would, in other markets, provide at least some guardrails. The legal frameworks are developing , Nigeria, Kenya, Ghana and South Africa have all made significant progress on data protection but the translation of law into day-to-day organisational practice remains incomplete.
Third, the consequences of a confidentiality breach are severe in any market, but in markets where trust is hard-won and reputational damage spreads quickly, the cost can be existential. A bank that leaks customer data, a law firm that loses privilege over client documents, a hospital that exposes patient information these are not recoverable inconveniences. They are breaches of the trust on which the entire business depends.

What African leaders must do now
The good news is that the solution is neither expensive nor complex. It does not require new technology. It requires leadership, clarity, and a small amount of disciplined effort.

First, establish a clear AI usage policy. A single, plain-language document that states what types of information may and may not be entered into AI tools. It does not need to be sophisticated. It needs to exist, and it needs to be communicated.

Second, train your people. Not a lengthy programme a clear, honest conversation. Most employees who create AI-related risk do so because nobody has explained the danger to them. Once they understand, the overwhelming majority adjust their behaviour immediately.

Third, create a record. The UK tribunal ruling makes clear that when accountability is tested, organisations will be expected to demonstrate that their people understood the rules. A simple, dated record showing that staff have received and acknowledged the AI usage policy is no longer an administrative nicety. It is a protection.

Fourth, lead by example. When senior leaders talk openly about responsible AI use, it gives everyone else permission to ask the questions they are currently afraid to ask.

The opportunity inside the warning
It would be easy to read this column as a reason to fear AI, or to restrict it. That is not my intention.

AI is one of the most powerful tools African professionals have ever had access to. It can close capability gaps, accelerate work, and allow small organisations to compete with much larger ones. The answer is not to ban it. The answer is to govern it.

The organisations that will thrive in the African AI economy are not the ones that move fastest or the ones that move most cautiously. They are the ones that move deliberately adopting AI with energy, and governing it with discipline.

The UK tribunal ruling is a warning. But it is a warning delivered early enough to act on. African leaders who read it, understand it, and act on it now will protect their organisations, their clients, and their reputations.

Those who treat it as someone else’s story will learn the same lesson later and at a far higher price.

The choice, as always, belongs to leadership.

Folu is AI Architect & Risk & Governance Director, United Kingdom, Founder of AIExpertsPro, and an AI governance advisor to UK and African financial institutions, and can be reached via aiexpertspro.co.uk/folu@aiexpertspro.co.uk

By Folu Adebayo 

Imagine arriving at work one morning to find that a decision has been made about your future. Not by your manager. Not by your CEO. Not even by a committee that reviewed your performance, your contributions, or your years of service.

By an algorithm.

And when you ask why, when you look across the room at the people who deployed that algorithm and ask them to explain how it reached its conclusion, they cannot tell you.

Not because they are hiding something. But because nobody thought to ask that question before they pressed the button.

This is not a hypothetical. It is happening right now. And it is coming to Africa faster than most leaders realise.

The numbers are staggering

In 2025 alone, nearly 55,000 job cuts were directly attributed to AI, according to Challenger, Gray & Christmas, out of a total 1.17 million layoffs, the highest level since the 2020 pandemic. The companies involved read like a who’s who of global business. Amazon. Workday. Meta. Google.

In early 2026, major firms including Meta, Google, Amazon, Block, Atlassian, Pinterest, and Salesforce announced significant layoffs while explicitly linking cuts to productivity gains from AI tools. Block cut close to 40% of its workforce more than 4,000 roles with leadership arguing that AI tools and flatter organisational structures are changing how companies are built and run.

Baker McKenzie, the global law firm, laid off between 600 and 1,000 employees up to 10% of its global workforce e4 as part of a shift towards AI, primarily affecting support staff including roles across research, marketing, and secretarial functions.

These are not small numbers. These are people’s livelihoods. Families’ security. Communities’ stability.

And in almost every case, the same question went unanswered: on what basis, exactly, did AI determine that these specific people should go?

“When an AI system makes a decision and those who deployed it cannot explain its reasoning, accountability evaporates.”

The accountability black box

Many AI systems operate as black boxes, obscuring decision-making processes that affect employment. This opacity complicates responsibility attribution when AI systems produce harmful outcomes.

This is the governance crisis hiding inside the AI revolution.

When a human manager makes a redundancy decision, there is a process. There is documentation. There is a legal obligation to demonstrate fairness. There is, at minimum, a person who must look the employee in the eye and take responsibility for the decision.

When an AI system makes or influences that same decision and the people who deployed it cannot explain its reasoning accountability evaporates. The employee loses their livelihood. The organisation faces reputational and legal risk. And somewhere in between, the question of who is responsible gets lost in the technical complexity.

This is not just a legal problem. It is a moral one.

AI-washing the new corporate cover

A January 2026 Forrester report was blunt: many companies announcing AI-related layoffs do not have mature, vetted AI systems. The term “AI-washing” has entered the business lexicon to describe companies that attribute workforce reductions to AI-driven efficiencies when the underlying reasons are more financially pedestrian.

In other words: some of these organisations are not using AI to make better decisions. They are using AI as a convenient explanation for decisions they had already made for other reasons.

This is a governance failure of a different kind. Not the failure to control AI but the failure to be honest about what AI is actually doing, or not doing, inside your organisation.

The research that should stop every board in its tracks

Companies reporting high ROI from AI were not the same ones reporting AI-related workforce reductions. “That’s not where the value is,” said one Gartner analyst. “That’s not where the productivity gains are going to be.”

Instead, the study found companies with the highest gains were those using AI as a form of people amplification implementing the technology to make workers more productive rather than outright replacing them.

Read that again.

The organisations getting the most value from AI are not the ones firing people. They are the ones making their people better.

The organisations firing people and attributing it to AI are, in many cases, getting worse returns, not better ones.

The narrative that AI necessarily means fewer people is not just ethically questionable. It is, according to the evidence, strategically wrong.

“Africa has a choice that companies already down this road did not fully exercise.”

What this means for African businesses

I want Nigerian and African business leaders to sit with this carefully.

The pressure to deploy AI is real. The competitive and cost arguments are real. And the global trend toward leaner organisations is real.

But Africa has something that the companies making these decisions in Silicon Valley and London often lack: the wisdom born of building in difficult conditions, the understanding that people are not just costs to be optimised, and the institutional memory of what happens to communities when employment disappears without accountability or explanation.

AI is not killing jobs outright, it is hollowing them out, steadily absorbing discrete tasks, narrowing roles, and compressing wages. Those whose work depends on judgment, context, and accountability may find a useful collaborator in AI. Everyone else may find themselves doing less, earning less, and wondering how it happened.

African organisations have a choice that the companies already down this road did not fully exercise. They can build AI governance frameworks that require explainability before deployment. They can insist that any AI system influencing employment decisions must be able to justify those decisions in plain language. They can hold their technology providers accountable for the outputs not just the inputs of their systems.

And they can choose, deliberately and explicitly, to use AI as the research suggests it works best: not to replace people, but to make them more capable.

The question every board must answer

If your organisation is using or planning to use AI in any process that touches employment — recruitment, performance management, workforce planning, redundancy selection — you must be able to answer one question before you proceed.

If an employee asks why this decision was made about them, can you explain it?

Not in technical terms. Not by pointing to a model. In plain, honest language that a reasonable person could evaluate and challenge if they believed it was wrong.

If you cannot answer that question, you are not ready to deploy that system.

The AI that fired 1,000 people and nobody could explain why a story about technology is not just.

It is a story about what happens when organisations deploy power without accountability.

Africa has seen that story before. In different forms, through different instruments.

We do not need to repeat it.

Folu is AI Risk & Governance Director, United Kingdom, Founder of AIExpertsPro, Neuohelp.ai, AI governance advisor to UK and African financial institutions. She writes weekly on AI governance and responsible technology for The Boss Newspaper.

aiexpertspro.co.uk  |  folu@aiexpertspro.co.uk