The "AI Layoff" Myth
AI is not taking your job.
We have all read the headlines and heard the narrative. Companies are claiming AI has enabled them to lay off thousands of workers. Chatbots are reportedly already filling all lower-level positions, making it difficult for graduates to find employment. Tech bro CEOs are preaching that AI is revolutionising the economy, and you need to get with the program or be left behind. But how much of this is actually true? What does the data actually reveal? Well, if you dig past the distorted Big Tech oligarchic propaganda, you will discover that this narrative is almost entirely bulls**t and couldn’t be further from the truth if they tried. Take the recent report from Oxford Economics (OE), which found that companies “don’t appear to be replacing workers with AI on a significant scale” and instead suggests that they are actually using the AI layoff narrative to cover up their own shortcomings.
The report debunks this industry propaganda in four main steps. So, let’s dive in.
Graduate Jobs
It is true that graduates’ unemployment rates have steadily risen since the launch of ChatGPT. You could understand how people might think this is an example of AI replacing workers because many people assume these lower-level jobs are easier to automate with AI. However, OE found that the rise in the unemployment rate isn’t due to AI but other external forces.
For example, OE found that there are simply more graduates than there used to be. Since 2019, the number of 22–27-year-olds with a university education in the US has risen from 32% to 35%. In Europe, the increase is even more noticeable, with the number of 25–29-year-olds with a university education going from 39% in 2019 to 45% by 2024. This has created a huge “supply-side surge” and means there aren’t enough graduate jobs to go around, which has affected unemployment rates.
Furthermore, OE analysis found that the rising graduate unemployment rate shows all the hallmarks of being caused by wider economic slowdowns.
During these slowdowns, graduate unemployment typically rises higher than the general unemployment rate, which is exactly what the OE data conveys. Additionally, graduate unemployment is not rising in other nations like South Korea and Japan that have implemented AI but have not experienced an economic downturn.
This is supported by other studies, such as Deutsche Bank’s, which found that AI investment is possibly preventing the US from entering a recession. In other words, the US is functionally experiencing an economic downturn, apart from Big Tech, which continues to invest in itself as part of a big, multi-company circlejerk. So, we should expect graduate unemployment to be rising sharply anyway.
This is a simple case of attribution error. Just because graduate unemployment began to rise at approximately the same time AI chatbots became widely accessible doesn’t mean that one caused the other. Correlation doesn’t equal causation.
The Productivity Surge?
One of the best lines from this report is when it directly asks, “If jobs are being replaced, where’s the productivity surge?” Everyone seems to have forgotten that productivity is something we measure, and if the AI rhetoric is true, that metric ought to be skyrocketing.
Unfortunately, across all major economies, productivity growth is actually slowing or stagnant. This appears to be connected to wider economic slowdowns once more, as these reduce productivity gains.
The report does highlight that it is dangerous to read too much into this kind of data. After all, this form of data is known to be quite volatile. However, what we can acknowledge is that the massive productivity gains we would expect to see if AI job automation were causing thousands of layoffs and skyrocketing graduate unemployment rates simply aren’t there. And that heavily implies that this narrative is false.
Reported Job Losses
One of the most damning points of the entire report is the fact that the layoff data itself doesn’t even support the AI rhetoric.
The OE highlighted data from Challenger, Gray & Christmas, a leading provider of layoff data, which found that AI was cited as the reason for nearly 55,000 U.S. job cuts in the first 11 months of 2025. That is a major escalation, as AI was cited as the reason for fewer than 20,000 U.S. job cuts across 2023 and 2024.
At face value, this data seems to endorse the AI rhetoric.
That is, until you realise that in the U.S. labour market, 1.5 million to 1.8 million workers lose their jobs in any given month. As such, these 55,000 job cuts represent just 4.5% of total reported job losses. That really isn’t very much.
Not to mention OE researchers believe even this figure is inflated.
“We believe that the extent of job losses attributed to AI is more likely to be overstated rather than understated. Linking job losses to increased AI usage rather than other negative factors like weak demand or excessive hiring in the past conveys a more positive message to investors.”
And I am inclined to agree with them. After all, this is self-reported data from employers, and they are desperate to look good, particularly in today’s difficult economy.
So, even if this figure is correct, AI is only replacing a tiny number of jobs. But even the experts believe this is a considerable overestimate.
AI Adoption Rates
Now, if the number of jobs being lost to AI is increasing, just as Challenger, Gray & Christmas suggests, then you would expect the AI adoption rates of corporations to also increase, right?
Interestingly, OE found that the AI adoption rates in corporations are starting to level off, or even reverse, for large corporations, which has been supported by multiple sources (read more here).
This strongly suggests that there is a significant misattribution of the reported job losses. The fact that there hasn’t been a productivity surge also suggests that corporations are beginning to realise that AI can’t automate jobs and doesn’t deliver the productivity gains it promised, so they are delaying the adoption of these tools. This, in turn, reinforces OE’s stance about the reasons behind graduate unemployment.
The Scale Problem
By making these four simple points, this OE report has totally unravelled the AI layoff narrative. But why hasn’t AI lived up to its own publicity?
Personally, I would point to the litany of studies which highlight just how utterly useless and god-awful AI is. But the good people at OE are much classier than me and proposed a simpler explanation.
AI efficiency gains do not necessarily scale up.
Sure, it might help you complete one task faster, but this can have negative spillover effects. The example OE provides is jobseekers using AI to apply for jobs. It may help the jobseeker be more ‘efficient’, but as OE put it, “If AI simply leads to more people applying for more jobs for which they are a poor fit, the overall gains from AI will be limited.”
Efficiency gains on a micro scale do not necessarily translate to the macro scale of a job or a business and definitely don’t translate to the mega scale of an entire economy. Again, as OE put it, “AI can enhance process efficiency, but summing the individual gains for a firm or the economy-wide impact may be misleading.”
For AI to actually have any meaningful impact on overall productivity or the job market, it needs to “address existing bottlenecks and new ones it creates.” Sadly, that isn’t how AI is being deployed, and a growing body of research from recent studies (MIT, PwC, METR, CMU, MIT Sloan, CMU, JYX) indicates that fundamental problems with the technology — such as hallucinations, cognitive debt, skill atrophy, etc. — make it detrimental to use in critical bottlenecks.
In other words, just because AI can help you write an email doesn’t mean it can replace workers, make a company more productive, or revolutionise the economy.
Summary
Quite simply, as the OE has beautifully shown, there is no credible evidence that AI layoffs are happening on a meaningful scale. What’s more, the OE even “suspects some firms are trying to dress up layoffs as a good news story rather than bad news, such as past over-hiring” as it “conveys a more positive message to investors.” The narrative we are being fed is total bulls**t. It is propaganda designed to paint techbros and CEOs in a better light and line their pockets with duped investor dollars. Not to mention there are plenty of studies out there that heavily suggest AI will never be able to cause mass layoffs, as the technology is simply too fundamentally flawed.
So, the next time someone tries to force this twisted narrative down your throat, take a second and ask why they want you to believe it. What do they gain from pulling the wool over your eyes? And what are you missing out on?
Thanks for reading! Everything expressed in this article is my opinion, and should not be taken as financial advice or accusations. Don’t forget to check out my YouTubechannel for more from me, or Subscribe. Oh, and don’t forget to hit the share button below to get the word out!
Sources: Oxford Economics, Fortune, Will Lockett, CNBC, Will Lockett, MIT, PwC, METR, CMU, MIT Sloan, CMU, JYX
I remember when computers were becoming the thing, mid to late 60s, I think? My Dad was an accountant for a big CPA firm and the computer they put in wouldn't fit in my two car garage!
But that certainly had an effect on employment, especially in an accounting world.