AI-washing: the real layoff story

Companies including Amazon and Pinterest have linked job cuts or restructuring to AI. Those announcements do not by themselves show which tasks AI is already performing.

A Forrester report published in January 2026 questioned those explanations. Many companies announcing AI-related layoffs, the analysts found, do not actually have mature AI applications ready to fill those roles. The report challenges whether AI is the immediate cause of those cuts.

What is AI-washing?

The term borrows from "greenwashing", where companies exaggerate their environmental credentials. AI-washing works the same way, but in reverse. Instead of overstating what AI can do for the planet, companies are overstating what AI can do for their workforce. They are attributing financially motivated cuts to future AI implementation that may never materialise.

As Molly Kinder, a senior research fellow at the Brookings Institute, put it: saying layoffs are caused by AI is a "very investor-friendly message." The alternative might mean admitting the business is struggling, that pandemic-era over-hiring created bloated teams, or that revenue targets were missed.

AI makes for a better press release than "we hired too many people in 2021."

The numbers tell a different story

More than 50,000 layoffs in 2025 were publicly attributed to AI. The total does not establish how many of those roles AI systems had already replaced.

Many of the companies making these cuts had not deployed AI tools at scale. Some had pilot programmes. Others had vague roadmaps. Very few had production-ready systems capable of replacing the roles they were eliminating.

This matters because it shapes public perception. Every AI-attributed layoff reinforces the narrative that automation is an unstoppable force already displacing workers en masse. That narrative creates anxiety, influences policy, and can distort strategic planning.

If your board reads that Amazon cut roles "because of AI" and then asks why your department has not done the same, you need to be armed with the reality behind the headlines.

But genuine disruption is real

The article distinguishes questionable layoff explanations from changes in work caused by AI adoption.

In the first week of February 2026, Anthropic launched a suite of AI tools targeting legal, sales, and customer support workflows. Share prices fell after the announcement. Shares in Pearson fell 8%. Relx plunged 14%. Thomson Reuters lost 18% in a single session. The FTSE 100, which had hit a record high that morning, was dragged into the red.

These are not speculative startups. These are established companies with decades of market dominance, and investors wiped billions off their valuations overnight because an AI company released a product.

Clifford Chance, one of the world's largest law firms, had already cut 10% of its London business services staff in November 2025, citing increased AI use as a genuine factor. According to Morgan Stanley, the UK is losing more jobs than it is creating as companies adopt AI tools and is being hit harder than rival economies including the US, Japan, Germany, and Australia.

Some companies are using AI as cover for unrelated cuts, while others are experiencing real displacement. The challenge for IT leaders is telling the difference.

How to spot AI-washing in your organisation

As someone who manages IT strategy across a complex business, I have learned to ask pointed questions when "AI" gets thrown around in boardroom conversations. Here is what I look for:

1. Is there a production-ready system?

If someone claims AI will replace a function, ask to see the tool. Not a demo. Not a proof of concept. A production system with documented accuracy, error rates, and a support model. If it does not exist yet, the layoff is not AI-driven. It is cost-driven with AI branding.

2. What is the transition plan?

Genuine AI-driven restructuring comes with a transition plan. Retraining programmes. Phased rollouts. Fallback procedures. If the plan is "cut now, automate later," that is a red flag.

3. Who benefits from the narrative?

Follow the incentives. If the company's share price responds positively to "AI transformation" messaging, there is a financial incentive to frame every cost reduction as AI-related, whether it is or not.

4. Are the affected roles actually automatable?

This is the most basic question and it is surprising how rarely it gets asked. Some roles being cut involve complex judgment, relationship management, or creative problem-solving that current AI simply cannot replicate. If those are the roles being eliminated "because of AI," something else is going on.

What IT leaders should actually be doing

Evaluate AI proposals against the work, tools and evidence available in your organisation.

Audit your AI readiness honestly. Map your current processes against what AI can genuinely automate today, not in some theoretical future. Be specific. Contract review? Possibly, depending on complexity. Strategic vendor negotiation? Not even close. My series on business AI enablement provides a structured framework for this assessment.

Build a skills transition framework. The roles that AI genuinely threatens tend to be repetitive, data-heavy, and rules-based. The people in those roles often have institutional knowledge that is incredibly valuable. A good IT leader finds ways to redeploy that knowledge rather than simply cutting headcount. Understanding the shadow AI governance crisis is part of this assessment. You need to know where AI is being used before assessing its workforce impact.

Push back on performative AI strategy. If your C-suite wants to announce an "AI transformation" without the underlying capability to deliver it, that is your moment to provide honest counsel. The short-term PR benefit is not worth the long-term credibility damage when the promised efficiencies fail to materialise.

Watch the tooling market closely. The Anthropic announcement moved markets because it represented a genuine capability leap. These moments will keep coming. Your job is to evaluate each one against your organisation's requirements and test results.

The honest conversation we need

Twenty-seven percent of UK workers are worried their jobs will disappear within five years because of AI. That anxiety is understandable, but it is being amplified by companies that are muddying the waters between genuine automation and convenient excuses.

IT leaders need to explain what the available evidence supports. That means being honest about what AI can and cannot do today. It means challenging AI-washing when we see it, even when the narrative is politically convenient. And it means preparing our organisations for changes supported by evidence rather than investor messaging. If you are looking for a practical starting point, AI training and closing the skills gap covers how to equip your workforce for the genuine changes that are coming.

Base workforce plans on tested systems, transition support and explicit limits on what the tools can do.

If you need an honest, independent perspective on AI strategy for your organisation, my IT management consulting practice can help you assess proposals against operational evidence.

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Daniel Glover is Head of IT Services at a major UK e-commerce business, managing a team across infrastructure, security, and digital transformation. He writes about technology leadership, AI strategy, and the realities of enterprise IT.