Half a million tech workers have lost their jobs since ChatGPT launched in late 2022. The conventional wisdom is clear: artificial intelligence is eating the workforce. But what if that narrative is, at best, incomplete—and at worst, a convenient fiction that lets corporations avoid accountability for ordinary business decisions?

New research from Oxford Economics challenges the AI displacement story that has dominated headlines for three years. According to the firm's analysis, "firms don't appear to be replacing workers with AI on a significant scale," suggesting companies may be using the technology as cover for headcount reductions that would have happened regardless of any technological revolution.

The Numbers Don't Add Up

The disconnect between AI hype and employment reality is striking. Companies have announced massive AI investments and promised revolutionary productivity gains, yet the aggregate data shows no corresponding surge in output per worker that would justify the layoff figures being attributed to automation.

"If AI were truly displacing workers at the scale companies claim, we would see it in the productivity statistics," noted one economist familiar with the Oxford research. "Instead, we see companies cutting costs during a period of economic uncertainty and blaming a technology that hasn't yet delivered on its promises."

Forrester's research adds another uncomfortable data point: 55% of employers report regretting layoffs they attributed to AI. That's more than half of companies essentially admitting they cut too deep or misjudged the technology's actual capabilities.

The Rehiring Shell Game

Perhaps the most damning finding concerns what happens after AI-attributed layoffs. Forrester predicts that half of positions eliminated in the name of artificial intelligence will be quietly rehired—but offshore or at significantly lower salaries.

This pattern suggests many AI layoffs are less about automation and more about labor arbitrage. The technology provides rhetorical cover for moving work to lower-cost jurisdictions, a practice that predates ChatGPT by decades but lacks the futuristic sheen that makes AI-related job cuts seem inevitable rather than cynical.

Entry-Level Elimination

The human cost of this strategy falls disproportionately on younger workers. Companies are eliminating entry-level positions at alarming rates, citing AI capabilities that can supposedly handle tasks that once provided on-ramps for new graduates. Yet Gen Z workers have the highest AI readiness scores of any generation—22% compared to just 6% for Baby Boomers—suggesting the workers being cut are precisely those best positioned to work alongside new technology.

"There's a cruel irony here," observed a workforce development researcher. "We're shutting out the generation most capable of leveraging AI by claiming AI makes them unnecessary."

Which Jobs Are Actually at Risk?

According to recruitment platform Indeed, the roles most commonly cut during AI restructuring are software engineers and developers, quality assurance engineers, product managers, and project managers. These are precisely the kinds of jobs that require judgment, creativity, and stakeholder management—capabilities where current AI systems remain notably weak.

True AI displacement, when it eventually arrives at scale, will likely look quite different. Routine cognitive tasks, data entry, basic analysis, and repetitive content generation are far more susceptible to automation than the strategic and interpersonal work that dominates the roles being eliminated today.

The Coming Reality Check

None of this means AI won't eventually transform employment. Venture capitalists predict 2026 will be "the year of agents," with AI expanding from productivity enhancement to actual work automation. Forrester projects that 30% of companies will replace specific HR and administrative functions with AI by year's end.

But the transition will be more gradual than the layoff announcements suggest. Only 16% of workers had high AI readiness in 2025, a figure projected to reach just 25% by the end of this year. The gap between technological potential and organizational capability to deploy it remains substantial.

For workers navigating this environment, the Oxford Economics research offers a counterintuitive form of reassurance: if your job was eliminated and blamed on AI, the actual reason may have been far more mundane. And if AI-attributed layoffs are indeed "corporate fiction," the path back to employment may be shorter than the dystopian headlines suggest.

The companies most aggressively cutting in AI's name may find themselves scrambling to rebuild capabilities they discarded too hastily. Those that take a more measured approach—investing in genuine human-AI collaboration rather than using technology as an excuse—will likely emerge stronger when the hype cycle finally gives way to productive reality.