The 'Dirty Secret' Behind AI Layoffs: Forrester Warns Tech Is Often Non-Existent

Executives are increasingly blaming artificial intelligence for sweeping layoffs even when the technology is barely in place, Forrester has warned, with analyst J.P. Gownder saying that in 'nine out of 10' such cases the AI capability behind those cuts simply does not exist.

The news came after a wave of job reductions at some of the world's biggest employers, many of which have been wrapped in the language of automation and digital reinvention. Nike has announced around 1,400 job cuts tied to restructuring and streamlining. Meta has reportedly moved to shed about 8,000 roles while spending heavily on AI infrastructure. Microsoft continues to reconfigure teams around AI priorities. On paper, this looks like a textbook technological revolution. Forrester's analysis suggests something more prosaic is often going on.

Forrester forecasts that AI and automation will eliminate 6.1% of US jobs, or about 10.4 million roles, by 2030. The number is stark, and the firm is not downplaying the disruption. What it does question is the neat story many boards now tell: that highly capable AI systems are already in place, ready to step neatly into the shoes of the people being shown the door.

The 'Dirty Secret' Of AI Layoffs, According To Forrester

Gownder and his team have spent months asking a simple question of companies announcing AI-driven layoffs: is there a mature AI system running at scale that can genuinely replace the affected roles? 'Nine out of 10 times, the answer is no,' he says.

If that is right, the 'dirty secret' behind many AI layoffs is that they are, in substance, old-fashioned cost cuts dressed in futuristic language. Forrester's January 2026 forecast expects generative AI to drive around half of all AI-related job displacement by 2030. Yet it also concludes that far more positions will be reshaped than abolished outright.

The tension is obvious. Current AI tools can draft, summarise and assist, but they are not magic workforce erasers. When executives imply otherwise, they invite problems on several fronts. Investors may overestimate how sophisticated the company's operations really are. Staff may assume powerful automation systems are already humming away in the background. Boards may even bake unrealistic productivity gains into their financial plans, only to scramble when the promised efficiencies fail to materialise.

Over time, that mismatch between AI rhetoric and AI reality does not just bruise reputations. It corrodes trust inside the organisation, where people are usually better placed than anyone to know what technology is actually running on the shop floor.

When AI Layoffs Become A Branding Exercise

Some companies have tried to steer clear of this trap. In Nike's internal briefings around its recent reduction, leadership reportedly stressed 'operational simplification,' technology restructuring and supply chain efficiency, casting the cuts as part of a broader turnaround and a move towards a 'leaner, faster and more agile organisation.' That is corporate language, certainly, but it stops short of insisting that AI systems are already taking over.

Others have been less careful, loudly presenting job losses as evidence of an AI transformation before any meaningful deployment has occurred. According to Forrester, some firms have subsequently faced sceptical questions from investors and visible resistance from employees once the gap between promise and reality became clear. There have even been cases, the research suggests, where roles had to be quietly rehired when the tools supposed to replace them could not reliably do the work.

Nothing in Forrester's report implies that AI layoffs are imaginary. Its own numbers confirm that millions of jobs will go. What it argues, with some force, is that sequencing matters. Too many boards are announcing AI-related cuts first and trying to build the AI capacity afterwards.

In theory, an organisation making people redundant in the name of AI should already have several building blocks in place. Forrester points to fully vetted systems operating across core workflows rather than in pilot mode, hard data showing productivity gains in specific processes, a plausible timeline for scaling those tools and a transition plan for workers, including retraining and redeployment where it makes sense. Where those foundations do not exist, management is essentially betting that underdeveloped technology will very quickly grow into the shape of the hole they have just punched in the organisation chart.

On the ground, it rarely works like that. Remaining staff inherit heavier workloads while leaders assume automation will 'fill the gap.' If the software underperforms, burnout follows, customers notice and the same executives who talked up their AI revolution find themselves scrambling to rebuild capacity.

AI Layoffs Are Real, But AI Work Is Changing Faster

The bigger story in Forrester's forecast is not the job cuts but the quieter rewiring of work. While 6.1% of US jobs are expected to be eliminated by 2030, the firm believes about 20% of roles will be significantly transformed by AI tools and new workflows. For every position lost, more than three may be meaningfully altered rather than erased.

Microsoft's recent moves broadly mirror that pattern. Although it has cut staff while reorienting around AI, much of its internal effort has gone into reorganising teams, introducing AI 'copilots' and redesigning workflows, rather than simply presenting AI as a blunt mechanism for headcount reduction.

In practice, that kind of change is messy. It means retraining employees to work alongside AI rather than be replaced by it. It means rewriting job descriptions and evaluation metrics. It means building entirely new management structures around AI-augmented teams and being honest, in public and in private, about where the tools are strong and where they are still experimental.

This is also where communication around AI layoffs begins to matter as much as the technology itself. Meta's workforce reductions earlier this year drew criticism in part because the external narrative leaned so heavily on AI investment while many inside the company felt the human cost received less clear acknowledgement.

Forrester's underlying message is awkward but not especially complicated. Yes, AI and automation will reshape labour markets. Yes, some companies will shrink as they modernise. But the organisations likely to emerge stronger are those whose AI layoffs are backed by functioning systems rather than PowerPoint slides, and whose leaders can resist the temptation to put buzzwords ahead of what their technology can actually do today.