Companies like Atlassian, Block, and Amazon have announced they will lay off thousands of employees due to their increased reliance on AI.
The stories these companies present are consistent. AI will replace human labor, and responsible business owners will need to adjust.
But the evidence tells a more nuanced story.
The automation story is partially true
Although there are genuine disruptions in certain areas of the labor market, the scale of the disruption is generally exaggerated. Anthropic research published earlier this month found that while many work tasks are susceptible to automation, the majority are still primarily performed by humans rather than AI tools.
Additionally, some occupations are more at risk of turnover than others. Computer programmers top the list, followed by customer service representatives and data entry workers. However, even among the most at-risk occupations, the use of AI remains limited.
Aggregated economic data reflects this reality. A 2025 Goldman Sachs report estimates that about 2.5% of U.S. jobs would be at risk of job loss if AI were used throughout the economy to do everything it can do today.
That’s not an insignificant number. However, the report notes that workers in jobs exposed to AI are currently less likely than anyone else to lose their jobs, face reduced hours, or receive lower wages.
The report points to early signs of tension in certain industries. Goldman Sachs identifies sectors where job growth is slowing in line with AI-related efficiency gains. Examples include marketing consulting, graphic design, office management, and call centers.
In the technology sector, the unemployment rate for U.S. workers in their 20s in jobs exposed to AI rose by almost 3% in the first half of 2025. Anthropic’s research also found that the job search rate (the probability of an unemployed person finding a job within a month) for workers aged 22 to 25 in jobs exposed to AI has fallen by about 14% since the launch of ChatGPT in 2022. It’s a tentative, but first signal of where pressure is being felt.
These are meaningful signals, but they are sector-specific and focused and not evidence of a full-scale population shift, as corporate announcements often suggest. This gap between evidence and rhetoric raises obvious questions. Are there other factors driving these decisions?
What is your motivation?
The timing and framework of layoffs resulting from AI-driven layoffs requires close investigation. Corporate restructuring, overemployment as demand for online services surges in the post-pandemic boom, and pressure from investors to show improved profit margins are all working at the same time as real advances in AI.
Although these are not mutually exclusive explanations, they are rarely recognized simultaneously in corporate communications.
There are strong economic incentives for companies to be seen as actively adopting AI. Since ChatGPT’s launch, AI stocks have accounted for about 75% of the S&P 500’s returns.
The layoffs, centered around the introduction of AI, are sending a signal to investors that simple cost-cutting announcements are not the answer. Companies that innovate around AI look much better off than firing employees for declining revenues or bad strategic decisions.
It is also important to distinguish between two types of redundancies. The first is until AI truly increases productivity, requiring fewer workers to produce the same output. In the second, layoffs are not a result of AI, but a way to fund it.
Meta explains this difference. The social media giant reportedly plans to lay off up to 20% of its workforce while spending $600 billion to build data centers and hire top AI researchers.
In this case, laid-off workers will not be replaced by AI today. They are subsidizing the AI that employers are betting on for the future.
more likely future
The overall picture will likely be one of transformation rather than exclusion. According to a recent report from PwC, employment is still increasing in most industries exposed to AI, but growth tends to be slower than in sectors not exposed to AI.
At the same time, wages in industries exposed to AI are rising roughly twice as fast as those in industries with little exposure to AI. Workers with AI skills earn an average wage premium of about 56% across industries analyzed.
Taken together, these data point to a flattening of the traditional workplace pyramid rather than mass migration. Companies will reduce the number of junior employees needed for routine analytical and administrative tasks, while experienced professionals who effectively deploy AI tools will be more productive and create more value.
AI is a consequential technology and will have a huge impact in the long run. The question is whether the dramatic AI-driven layoffs announced by individual companies accurately reflect their trajectory, or whether they confuse true technological change with decisions that would have been made independently.
Making this distinction is not just an academic exercise. It shapes how policy makers, educators, and workers themselves understand the nature of the disruptions they face.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
