Surging AI adoption doesn’t match mass layoff narrative

Despite growing headlines linking artificial intelligence investments to workforce reductions, new Gartner research suggests AI itself is not yet a major driver of layoffs—and supply chain leaders risk making strategic workforce mistakes if they overreact to the narrative.

That was one of the core messages delivered by Thomas O’Connor, senior director analyst with Gartner, during a recent Gartner Supply Chain Symposium/Xpo presentation examining the relationship between AI and workforce reductions. The research analyzed more than 1.1 million jobs impacted across 255 companies during the second half of 2025.

“Layoffs were not an AI-driven story [in the second half or 2025] and indications are it hasn’t accelerated year-to-date in 2026,” Gartner stated in the presentation.

AI layoff narrative lacks data

According to Gartner’s analysis, only about 1% of job losses studied were tied directly to AI productivity gains. Less than 5% were related to hiring restraint, where companies froze hiring or avoided backfilling positions as AI tools increased productivity among existing workers. The overwhelming majority of workforce reductions stemmed from broader macroeconomic factors or strategic repositioning within large technology firms.

The findings mirror conclusions reached by Gallup in separate workforce research. In a recent survey of workers who had experienced layoffs, only a small fraction identified AI as the primary reason for losing their jobs, suggesting that public concern about AI-driven job displacement remains significantly larger than the impact currently being measured in the labor market.

“We analyzed over 1.1 million jobs after 2025,” O’Connor said in an interview with Supply Chain Management Review following the presentation. “Within this, we basically said, okay, so what are the types of workforce reductions that we’re seeing?”

O’Connor said there were basically three types of reductions. Those include “reduce,” where companies directly eliminate jobs due to AI productivity gains; “restrain,” where organizations slow hiring because existing employees using AI can absorb more work; and “reposition,” where companies shift resources from slower-growth areas into AI-focused growth initiatives.

O’Connor said the repositioning category—particularly among large technology firms such as Amazon, Microsoft, Meta, and Block—is driving much of the public perception surrounding AI layoffs.

“When you see what Meta’s doing, what Block’s done, what Microsoft’s done, Amazon’s done, all these big tech folk, they’re repositioning to take those funds and stick it into their AI growth engine,” O’Connor said. “That’s the play that’s going on.”

The broader issue, he argued, is that many organizations and employees are extrapolating a future scenario from a relatively small set of highly visible examples.

“We’re extrapolating forward what we are worried could potentially happen,” O’Connor said. “That’s what the data tells us today.”

Why workers fear AI

That concern appears to be spreading faster than actual workforce reductions. Gallup research found that nearly one in five workers believes AI or automation could eliminate their job within the next several years, highlighting a growing disconnect between employee perceptions and current labor market realities.

At the same time, AI adoption continues to accelerate. Gallup reports that AI usage in the workplace has more than doubled over the past two years, with roughly half of employees now using AI in some capacity. Yet despite that rapid growth, large-scale AI-driven layoffs have not materialized, reinforcing Gartner’s view that organizations are still in the early stages of workforce transformation.

From AI layoffs to AI strategies

The Gartner presentation emphasized that organizations should avoid assuming AI-driven workforce reductions are inevitable or immediate. Instead, Gartner recommends that companies focus on developing AI talent strategies rather than AI layoff strategies.

“Recognize you likely don’t need an AI layoff strategy,” O’Connor advised in the presentation. “You need an AI talent strategy.”

That strategy should focus on prioritizing AI investments, retaining critical employees, creating new career paths, and accelerating employee experience development.

The hidden risk: experience starvation

O’Connor said one of the biggest long-term workforce risks may not be widespread layoffs, but rather “experience starvation” caused by companies reducing or slowing hiring for entry-level office-based roles.

Gartner’s research divides workers into four workforce archetypes: “keystones,” which include frontline operational roles; “stewards,” or experienced operational employees; “protégés,” or less experienced future leaders; and “maestros,” or senior leaders and decision-makers.

The concern, O’Connor said, is that AI increasingly enables experienced employees to perform work previously handled by junior workers, potentially reducing the traditional developmental pipeline organizations rely on to build future leadership.

“The maestros, those senior people who are used to dealing with complexity, increasingly they can use AI to do some of the stuff the more junior folk could do,” O’Connor said. “And so you’re thinking about it very much around how do we retain those people because if we lose them, it’s going to be a bigger loss now than it would have been in the past.”

The trend is already beginning to appear in broader workforce data. Gallup has found that managers and senior leaders tend to adopt AI tools more rapidly than frontline employees, raising questions about how organizations will continue developing future talent if experienced workers increasingly absorb tasks that once served as training opportunities for junior staff.

At the same time, Gartner argues organizations cannot simply eliminate traditional entry-level work without redesigning future career pathways.

“If we’re getting rid of our graduate programs, then we’ve got to be asking ourselves, what are we actually doing in terms of our future state?” O’Connor said. “There has to be a new opportunity that we’ve got to identify.”

O’Connor pointed to Procter & Gamble as one example of a company already restructuring planning roles around AI-enabled decision-making. According to O’Connor, the company is redesigning some planning positions into new roles such as “supply flow analyst” and “supply flow engineer” where employees increasingly focus on decision orchestration and analytical oversight rather than manual planning tasks.

Automation, not AI, is the biggest threat

While AI itself may not yet be driving major workforce reductions, O’Connor said automation remains a much larger source of actual supply chain job displacement today.

“The biggest challenge when it comes to jobs in supply chain of where jobs may actually be lost is automation,” he said. “When you’re putting in a new, fully automated distribution center or automated factory, and you’re replacing one that was not, that is absolute job loss.”

Still, Gartner cautioned against viewing the current environment through a purely dystopian lens. The company’s presentation repeatedly stressed that media narratives surrounding AI layoffs often fail to reflect the broader labor market reality. One Gartner slide noted that “misinterpreting current events will lead to a serious strategic error.”

O’Connor believes organizations should focus less on headline-driven fear and more on practical workforce evolution.

“We don’t see a massive reduction in workforces broadly across the economy,” he said. “We’re still hiring people into our business. We’re just having to re-profile what the job description looks like.”

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