I've been tracking AI-driven layoffs for the past few months and something doesn't add up.
Block cut 4,000 people (40% of workforce). Atlassian cut 1,600. Shopify told employees to prove AI can't do their job before asking for headcount. The script is always the same: CEO cites AI, stock ticks up.
But then you look at the numbers. S&P Global found 42% of companies abandoned their AI initiatives in 2025, up from 17% the year before. A separate survey found 55% of CEOs who fired people "because of AI" already regret it. Klarna bragged AI could replace 700 employees, then quietly started hiring humans back when quality tanked.
What I keep seeing across the research is that AI compressed execution speed dramatically; prototyping that took weeks now takes hours. But the coordination layer (approval chains, quarterly planning, review cycles) didn't speed up at all. The bottleneck flipped from "can we build it fast enough" to "does leadership know what to build and can they keep up with the teams building it."
Companies are cutting the people who got faster while leaving the layer that didn't speed up intact.
Monday.com is an interesting counter-example. Lost 80% of market value, automated 100 SDRs with AI, but redeployed them instead of firing them. Their CEO's reasoning: "Every time we eliminate one bottleneck, a new one emerges."
I pulled together ten independent sources on this — engineers, economists, survey data, executives — and wrote it up here if anyone wants the full analysis with sources: https://news.future-shock.ai/ai-didnt-replace-workers-it-outran-their-managers/
Curious if anyone else is seeing this pattern in their orgs. Is the management layer adapting or just cutting headcount and calling it an AI strategy?
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