AI Layoffs Aren’t Working (And Nobody’s Talking About Why It’s Hilarious)

Imagine firing your customer service department and installing a chatbot that adds 260 chicken nuggets to ice cream orders. You stand in front of Wall Street and say, “Look at all these savings!”

Sound absurd? Welcome to 2026.

The Gartner Wake-Up Call

On May 11, Fortune published a Gartner study of 350 global executives with at least $1 billion in revenue. Finding: companies that laid off workers for AI are not getting the returns they promised.

The people you fire for saving money? Their absence doesn’t save money. The tech that replaced them? Doesn’t work well enough to replace them. You fired the wrong people.

Helen Poitevin, Gartner VP: “Chasing value only through headcount reduction is likely to lead most organizations down a path of limited returns.” Translation: your spreadsheet lied to you.

The Math That Makes No Sense

80% of companies that piloted AI reported workforce reductions
Those companies cut jobs regardless of whether AI was generating returns
Companies with the highest AI ROI weren’t firing people — they were making kept employees more productive
Workforce reduction rates were nearly equal across all ROI levels

Firing people for AI has nothing to do with getting better outcomes. Everyone just fired people. Then waited for returns that never came.

Klarna: The Poster Child

In 2023, Klarna bragged about replacing 700 customer service employees with an AI chatbot. Their CEO said AI could do “all of the jobs that we, as humans, do.” Wall Street clapped.

Reality hit. Complaints surged. Chatbots proved to be a velvet rope — a filter designed to frustrate you before reaching whatever human remained. By May 2025, the CEO admitted they “went too far” and started rehiring.

“There will always be a human if you want,” he said. Yes. Yes, it is.

Why This Keeps Happening

The boardroom spreadsheet. Subtract humans, add AI, rename the damage as “efficiency.” The people removed from the cost column are the same species expected to generate revenue in other companies’ columns.

Anticipated vs. demonstrated capabilities. Most AI-driven layoffs were based on future AI capabilities, not current performance. Companies fired people for technology they were never trained to use.

The knowledge destruction problem. The people who understood exceptions and edge cases carried institutional memory that doesn’t exist in any training dataset. You can’t fine-tune your way back.

The Better Way

PwC’s 2025 Global AI Jobs Barometer analyzed nearly a billion job postings: industries most exposed to AI saw 3x higher revenue growth per employee than the least exposed. Not because they fired people. Because they made people more productive.

Workers with AI skills command a 56% wage premium. Between 2019 and 2024, even highly automatable occupations saw 38% job growth. Far from apocalyptic.

The Bottom Line

The whole AI layoff story is funny because it’s true. The Jevons paradox — making coal more efficient increased coal demand — applies here. AI makes work more efficient, and smart companies are discovering it creates more work, more revenue, and more jobs.

The people who fired their way into obsolescence didn’t lose to AI. They lost to basic economics.

Quiz Time

1. What did the Gartner study find about AI layoffs and ROI? A) Companies that laid off workers saw 3x higher returns B) Workforce reduction rates were equal regardless of AI ROI outcomes C) AI layoffs only worked in the technology sector D) 80% reported immediate positive returns

2. What is the Jevons paradox? A) Making tasks cheaper increases overall demand for those tasks B) Every AI breakthrough is immediately regulated C) Companies adopting AI first always fail D) Chatbots cost more than human workers

3. How much higher was revenue growth per employee in AI-augmented industries? A) 1.5x B) 2x C) 3x D) 5x

Answers: 1-B, 2-A, 3-C