Companies such as Atlassian, Block and Amazon have announced they would lay off thousands of employees due to increased reliance on AI.
The narrative these companies offer is consistent: AI is making human labour replaceable, and responsible management demands adjustment.
The evidence, however, tells a more nuanced story.
The automation story is partly true
Genuine disruption is visible in specific corners of the labour market, though the scale of that disruption is commonly overstated. Research from Anthropic published earlier this month shows that although many work tasks are susceptible to automation, the vast majority are still performed primarily by humans rather than AI tools.
Moreover, some occupations are more exposed to displacement than others: computer programmers sit at the top of the list, followed by customer service representatives and data entry workers. Yet even within the most exposed occupations, AI use is still limited.
The aggregate economic data reflects this reality. A 2025 Goldman Sachs report estimated that if AI were used across the economy for all the things it could currently do, roughly 2.5% of US employment would be at risk of job loss.
That’s not a trivial number. However, the report notes that workers in AI-exposed occupations are currently no more likely to lose their jobs, face reduced hours, or earn lower wages than anyone else.
The report does note early signs of strain in specific industries. Goldman Sachs identifies sectors where employment growth has slowed that align with AI-related efficiency gains. Examples include marketing consulting, graphic design, office administration and call centres.
In the tech sector, US workers in their 20s in AI-exposed occupations saw unemployment rise by almost 3% in the first half of 2025. Anthropic’s research also found that job-finding rates (the chance of an unemployed person finding a job in a one-month period) for workers aged 22–25 entering AI-exposed occupations have fallen by around 14% since the launch of ChatGPT in 2022. This is a tentative but telling signal about where the pressure is being felt first.
These are meaningful signals, but they are sector-specific and concentrated – not the evidence of sweeping displacement that corporate announcements often imply. That gap between the evidence and the rhetoric raises an obvious question: what else might be driving these decisions?
What is the motive?
The timing and framing of the layoffs attributed to AI layoffs warrants closer examination. Corporate restructuring, over-hiring during the post-pandemic boom as demand for online services soared, and pressure from investors to demonstrate improved profit margins are all forces operating at the same time as genuine advances in AI.
While these are not mutually exclusive explanations, they are rarely acknowledged alongside one another in corporate communications.
There is a powerful financial incentive for companies to be seen to be embracing AI aggressively. Since the launch of ChatGPT, AI-related stocks have accounted for about 75% of S&P 500 returns.
A workforce reduction framed around AI adoption sends a signal to investors that a straightforward cost-cutting announcement does not. A company making AI-related innovations looks a lot better than one sacking staff due to declining revenues or poor strategic decisions.
It is also worth distinguishing between two kinds of workforce reduction. In the first, AI genuinely increases productivity to the point where fewer workers are needed to produce the same output. In the second, staff reductions are not a consequence of AI, but a way to fund it.
Meta illustrates this distinction. The social media giant is reportedly planning to lay off as much as 20% of its workforce, while simultaneously committing US$600 billion to build data centres and recruit top AI researchers.
In this case, the workers being let go are not being replaced by AI today; they are subsidising the AI bet their employer is making on the future.
The more plausible future
The big picture is likely one of transformation rather than elimination. According to a recent PwC report, employment is still growing in most industries exposed to AI, although growth tends to be slower than in less exposed sectors.
At the same time, wages in AI-exposed industries are rising roughly twice as fast as in those least touched by the technology. Workers with AI skills command an average wage premium of about 56% across the industries analysed.
Together, the data points toward a flattening of the traditional workplace pyramid rather than mass displacement. Firms require fewer junior employees for routine analytical and administrative work, while experienced professionals who deploy AI tools effectively become more productive and command greater value.
AI is a consequential technology and will have a significant impact in the long term. What is in doubt is whether the dramatic, AI-attributed workforce reductions announced by individual companies accurately reflect that trajectory, or whether they conflate genuine technological change with decisions that would have been made regardless.
Making this distinction is not merely an academic exercise. It shapes how policymakers, educators and workers themselves understand the nature of the disruption they are navigating.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
