A lot of companies are cutting staff to fund their AI programs. Gartner’s latest research shows that move is almost never paying off.

In a report published May 5, Gartner surveyed 350 global business executives from organisations with at least $1 billion in annual revenue that are actively using or testing AI agents, intelligent automation, or autonomous technologies. The finding that should stop every CEO in their tracks: roughly 80% of these organisations have reduced their workforce as part of their autonomous business strategy. And those cuts are not generating better returns.

Workforce reduction rates were almost identical between companies reporting strong ROI and companies reporting modest gains or outright losses. In other words, the layoffs are not the variable that determines success.

Helen Poitevin, Distinguished VP Analyst at Gartner, put it directly: “Many CEOs turn to layoffs to demonstrate quick AI returns. However, this disposition is misplaced. Workforce reductions may create budget room, but they do not create return.”

What Is Actually Working

The organisations that are seeing real ROI from autonomous business are doing something different. They are investing more in people, not less. Specifically, they are building new skills, creating new roles, and redesigning operating models so that humans can guide and scale autonomous systems effectively.

That is a fundamentally different posture than the one most companies are taking. Instead of asking “how do we automate this job away?” the winning organisations are asking “how do we give our people better tools so they can operate at a higher level?”

This maps to something most experienced operators already understand intuitively, and what BCG found in its own workforce research: AI amplifies the person using it. A good analyst with AI does the work of three. A poor operator with AI just makes mistakes faster. The human layer still matters enormously.

The Market Context

The stakes here are significant. Gartner forecasts AI agent software spending will reach $206.5 billion globally in 2026, growing to $376.3 billion in 2027. That is a market that is moving extremely fast, and most organisations are still figuring out how to get returns from what they have already deployed.

The autonomous business category, which encompasses AI agents, intelligent automation, and self-directed systems, is genuinely transformative technology. But transformative technology has always required human expertise to realise its potential. This is not unique to AI.

Gartner also projects that autonomous business will ultimately become a net-positive job creator, with new categories of roles expected to emerge by 2028 and 2029 that AI simply cannot fill. The pattern mirrors what happened with previous waves of automation: short-term displacement followed by a longer-term expansion of the types of work humans do.

What This Means for Business

If you are considering workforce reductions to fund your AI program, this research suggests you are solving the wrong problem.

The companies seeing returns are not the ones that eliminated headcount. They are the ones that redesigned how people work alongside autonomous systems, invested in building new capabilities across their teams, and treated AI as a multiplier rather than a replacement.

That distinction matters practically. It means the ROI question for AI is not “how many seats can we cut?” It is “how much more can our existing people accomplish with the right tools?”

For most businesses, this requires two things working together. First, the right AI infrastructure, agents, and workflows that actually integrate into how work gets done. Second, the people capability to work effectively with those systems, which does not happen automatically just because the tools are deployed.

Organisations that invest in both sides of that equation are the ones Gartner’s data says are winning.

The companies that cut first and upskill never are discovering that they freed up budget but lost the human expertise needed to actually capture the AI opportunity. That is a painful and expensive lesson to learn at scale.

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Enterprise DNA helps organisations on both sides of this equation. The EDNA Learn platform builds genuine AI and data capability across teams, turning the tool access your people already have into measurable performance. And Omni by Enterprise DNA deploys AI agents and workforce solutions designed to amplify your team, not route around them. If you are working through what an AI-driven operating model actually looks like for your business, that conversation starts here.