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
