AI gets the blame for 55,000 layoffs, but CFOs are the real culprits

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If you’ve been doomscrolling LinkedIn and wondering whether a robot stole everyone’s job this year, here’s some mildly comforting news: it mostly didn’t. 

Yes, companies cut about 1.1 million jobs this year, the worst bloodbath since the COVID-era layoffs, but AI was directly blamed for only around 55,000 of them. 

That’s less than one percent, according to data from Challenger, Gray & Christmas. (Via: Gizmodo)

Still, AI has become the villain of choice. Tech companies in particular have leaned hard into the narrative that layoffs are part of a sleek, futuristic “modernization” effort. 

When Amazon started prepping cuts in June, CEO Andy Jassy told employees AI would mean “fewer people doing some of the jobs that are being done today.” 

Fast-forward to October, after 14,000 people were shown the door, and Jassy told investors the decision wasn’t really AI-driven, “not right now at least.”

That doesn’t mean AI hasn’t cost anyone work. Companies like Salesforce have openly bragged about replacing humans with automation, claiming AI now handles up to 50 percent of certain workloads. 

But the bigger effect isn’t mass firings, it’s hiring freezes. 

Entry-level roles are quietly disappearing as companies convince themselves that a chatbot can do a junior employee’s job, even when it absolutely cannot.

Adding to the irony, an MIT study published this summer found that 95 percent of organizations running AI initiatives have seen zero financial return. That’s right: no profit, plenty of PowerPoint decks.

So what’s really happening? In many cases, companies overhired during the pandemic boom and are now trimming payroll as margins tighten. 

Others are feeling the effects of economic turbulence tied to tariffs from the Donald Trump era. 

Manufacturing alone has lost nearly 60,000 jobs this year, despite massive data center construction projects nationwide. Spoiler: AI didn’t swing the axe there.

In fact, Challenger’s data shows layoffs blamed on restructuring were more than double those blamed on AI. 

Cuts tied to market conditions were four times higher, and government efficiency-related cuts were nearly six times higher.