Tech firms are blaming layoffs on AI, however what’s actually occurring?

Uri Gal of the College of Sydney discusses the components impacting the working panorama and tech-based jobs.

Previously few months, a wave of tech firms have introduced important employees cuts and attributed them to effectivity good points pushed by synthetic intelligence (AI).

Firms reminiscent of Atlassian, Block and Amazon have introduced they might lay off 1000’s of workers as a consequence of elevated reliance on AI.

The narrative these firms supply is constant: AI is making human labour replaceable, and accountable administration calls for adjustment.

The proof, nonetheless, tells a extra nuanced story.

The automation story is partly true

Real disruption is seen in particular corners of the labour market, although the size of that disruption is usually overstated. Analysis from Anthropic revealed earlier this month exhibits that though many work duties are vulnerable to automation, the overwhelming majority are nonetheless carried out primarily by people somewhat than AI instruments.

Furthermore, some occupations are extra uncovered to displacement than others: pc programmers sit on the prime of the checklist, adopted by customer support representatives and knowledge entry staff. But even inside probably the most uncovered occupations, AI use continues to be restricted.

The mixture financial knowledge displays this actuality. A 2025 Goldman Sachs report estimated that if AI had been used throughout the financial system for all of the issues it might at the moment do, roughly 2.5pc of US employment can be prone to job loss.

That’s not a trivial quantity. Nonetheless, the report notes that staff in AI-exposed occupations are at the moment no extra more likely to lose their jobs, face decreased hours, or earn decrease wages than anybody else.

The report does be aware early indicators of pressure in particular industries. Goldman Sachs identifies sectors the place employment progress has slowed that align with AI-related effectivity good points. Examples embrace advertising consulting, graphic design, workplace administration and name centres.

Within the tech sector, US staff of their 20s in AI-exposed occupations noticed unemployment rise by virtually 3pc within the first half of 2025. Anthropic’s analysis additionally discovered that job-finding charges (the possibility of an unemployed particular person discovering a job in a one-month interval) for staff aged 22–25 getting into AI-exposed occupations have fallen by round 14pc for the reason that launch of ChatGPT in 2022. It is a tentative however telling sign about the place the stress is being felt first.

These are significant alerts, however they’re sector-specific and concentrated – not the proof of sweeping displacement that company bulletins usually indicate. That hole between the proof and the rhetoric raises an apparent query: what else could be driving these selections?

What’s the motive?

The timing and framing of the layoffs attributed to AI layoffs warrants nearer examination. Company restructuring, over-hiring throughout the post-pandemic growth as demand for on-line providers soared, and stress from traders to exhibit improved revenue margins are all forces working similtaneously real advances in AI.

Whereas these aren’t mutually unique explanations, they’re hardly ever acknowledged alongside each other in company communications.

There’s a highly effective monetary incentive for firms to be seen to be embracing AI aggressively. Because the launch of ChatGPT, AI-related shares have accounted for about 75pc of S&P 500 returns.

A workforce discount framed round AI adoption sends a sign to traders {that a} simple cost-cutting announcement doesn’t. An organization making AI-related improvements appears to be like loads higher than one sacking employees as a consequence of declining revenues or poor strategic selections.

Additionally it is value distinguishing between two sorts of workforce discount. Within the first, AI genuinely will increase productiveness to the purpose the place fewer staff are wanted to provide the identical output. Within the second, employees reductions aren’t a consequence of AI, however a option to fund it.

Meta illustrates this distinction. The social media big is reportedly planning to put off as a lot as 20pc of its workforce, whereas concurrently committing $600bn to construct knowledge centres and recruit prime AI researchers.

On this case, the employees being let go aren’t being changed by AI right this moment; they’re subsidising the AI guess their employer is making on the longer term.

The extra believable future

The large image is probably going one in every of transformation somewhat than elimination. In keeping with a current PwC report, employment continues to be rising in most industries uncovered to AI, though progress tends to be slower than in much less uncovered sectors.

On the similar time, wages in AI-exposed industries are rising roughly twice as quick as in these least touched by the know-how. Staff with AI expertise command a mean wage premium of about 56pc throughout the industries analysed.

Collectively, the info factors towards a flattening of the standard office pyramid somewhat than mass displacement. Corporations require fewer junior workers for routine analytical and administrative work, whereas skilled professionals who deploy AI instruments successfully turn out to be extra productive and command better worth.

AI is a consequential know-how and can have a major influence in the long run. What’s unsure is whether or not the dramatic, AI-attributed workforce reductions introduced by particular person firms precisely replicate that trajectory, or whether or not they conflate real technological change with selections that might have been made regardless.

Making this distinction isn’t merely an instructional train. It shapes how policymakers, educators and staff themselves perceive the character of the disruption they’re navigating.

Uri Gal

Uri Gal is a professor of Enterprise Data Methods on the College of Sydney Enterprise College. His analysis focuses on the organisational and moral points of digital applied sciences. He’s significantly within the relationships between individuals and know-how, and within the adjustments within the nature of labor related to the introduction of algorithmic applied sciences.

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