The Numbers Are In: Firing People Doesn’t Make AI Work Better
Here’s the thing about cutting jobs and blaming AI: it turns out the math doesn’t add up. Gartner surveyed large enterprises and found 80% had laid off employees after launching AI initiatives, with average reductions of 1–15% of headcount. But — and this is the kicker — there’s zero correlation between those layoffs and actual AI ROI.
Companies reporting strong AI returns cut staff at the same rate as companies reporting negative ROI. The layoffs and the returns aren’t connected. At all.
Gartner analyst Helen Poitevin put it plainly: “You would anticipate that those who are getting the most ROI maybe then are able to cut the most, but that’s not what we see. There seems to be no link between laying people off and getting ROI from AI investments.”
🔍 THE BOTTOM LINE
AI layoffs are cost-cutting theatre — and now Gartner has the data to prove it.
So What Actually Drives AI Returns?
Not firing people. That’s the headline from Gartner’s late 2025 survey of business executives at large enterprises.
The companies seeing real ROI from AI are doing the opposite: they’re reinvesting in their workforce. Training employees to build their own AI agents. Creating new roles for orchestrating autonomous systems. Building career paths for workers displaced by automation.
“They’re investing in upskilling people to be able to actually build their own agents or their own automations to get things done,” Poitevin said. “They’re enabling people to do some innovation on their own.”
What is AI upskilling ROI? It’s the measurable business return that comes from training existing employees to work alongside AI tools, rather than replacing them. Companies that invest in human-AI collaboration see productivity gains, innovation, and actual returns on their AI spend — while those that cut staff first are left trying to automate expertise they no longer have.
The Layoff Narrative Falls Apart
We’ve been tracking the AI layoff wave at Singularity.Kiwi for months — 92,000 tech jobs cut in 2026 alone, Meta cutting 8,000, Amazon restructuring 16,000, and Block firing 40% of its workforce to “focus on AI.”
The Gartner data confirms what we’ve suspected all along: the “AI is replacing jobs” narrative is, in most cases, a convenient cover for what’s really happening — corporate restructuring, cost-cutting, and over-hiring corrections from the pandemic boom years.
Andy Williamson, CEO of ONLC Training, noted that some recent “AI layoffs” appear to be misplacing blame for over-hiring. And some companies are already rehiring workers they let go, having discovered AI can’t actually replace the institutional knowledge they eliminated.
The Hard Truth: You Can’t Automate Expertise You No Longer Have
Brian Behe, CTO of RIIG Technology, nailed it:
“The organizations getting real returns are the ones that took the people who understood their business deeply and gave them AI tools to do more with that knowledge. The ones that cut first and automated second are now discovering that the institutional knowledge they eliminated was exactly what the AI needed to work properly.”
This is the paradox nobody in the C-suite wants to admit: AI doesn’t replace expertise — it amplifies it. But only if the expertise is still in the building.
Cut the people who understand the business, and you’ve cut the context the AI needs to be useful. The result? Expensive AI projects that deliver mediocre outcomes and a thinner workforce that can’t course-correct.
Gartner’s Advice: Don’t Use AI as an Excuse
Gartner’s recommendation is blunt: “Do not use AI as an excuse, especially if you want to get AI value.”
Poitevin’s direct quote: “People fear that AI could really do their whole job a lot less than they fear that their CEO thinks AI could do their full job.”
That’s a devastating observation. Workers aren’t afraid of the technology — they’re afraid of leadership that misunderstands it.
Williamson recommends an “automate-to-augment” strategy: automate routine tasks, then redirect freed-up talent toward higher-value work. It’s not complicated. It’s just not as easy as firing people and calling it transformation.
What This Means for Workers
If you’re in a role that’s been labelled “AI-at-risk,” the Gartner data offers some genuine relief:
- Layoffs don’t correlate with AI success. Companies cutting jobs aren’t the ones getting AI returns. Your job being “restructured” says more about your CEO’s strategy than AI’s capability.
- Upskilling is the path to ROI — and job security. The companies winning at AI are training their people, not replacing them.
- The boomerang is real. Companies that over-cut are rehiring because they need human expertise to make AI work.
- Forrester found 55% of employers regret their AI layoffs. That number will likely grow as the Gartner data circulates.
❓ Frequently Asked Questions
Q: What does this mean for NZ workers? NZ’s smaller companies may actually have an advantage here — with less pressure from activist investors to cut headcount, they’re more likely to invest in upskilling. The NZ tech sector should watch this data closely before following Silicon Valley’s lead on layoffs.
Q: Is Gartner saying AI doesn’t replace jobs? Not exactly. They’re saying the companies getting value from AI are augmenting workers, not replacing them. AI will transform 32 million jobs a year globally, Gartner predicts — but the ones seeing returns are using it to amplify human work, not eliminate it.
Q: What should I do if my company announces AI-driven layoffs? Ask hard questions. The data shows layoffs don’t improve AI outcomes. If your company is cutting staff in the name of AI efficiency, it may be a cost-cutting move dressed up as transformation. Invest in your own AI skills — companies that upskill are the ones actually winning.
🔍 THE BOTTOM LINE
The Gartner data is a gut punch to the “AI will replace your job” narrative that CEOs have been using to justify layoffs. The companies actually seeing returns from AI? They’re training people, not firing them. The ones cutting staff? They’re just cutting costs and calling it innovation — and now we have the numbers to prove it.
Sources
- Gartner — “Autonomous Business and AI Layoffs May Create Budget Room But Do Not Deliver Returns” (May 2026)
- CIO.com — “AI-driven layoffs aren’t making business sense” (May 2026)
