The AI blindspot: Layoffs are piling up, but where are the returns?
But a major global study by technology research firm Gartner reveals that companies’ rush to lay off workers may be the wrong strategic move. According to their data, staff cuts may temporarily free up cash in the budget, but would completely fail to deliver real financial returns on AI investments. This growing paradox suggests that real business value comes from expanding what human employees can do, rather than getting rid of them altogether.
Gartner warning: Why laying off staff may fail to boost AI profits
The Gartner research provides a clear warning to corporate leaders who view staff cuts as a shortcut to technology profitability. The main message of the report is that autonomous jobs and AI will not actually deliver returns. Rather than eliminating positions, Gartner recommends that organizations invest heavily in skills, roles, and operating structures that enable people to guide, manage, expand, and transition to autonomous capabilities.
Also Read | Meta reveals plans for layoffs and restructuring on May 20; Closed 6,000 open roles
The data highlights a huge disconnect between reducing headcount and making money. Nearly 80 percent of organizations currently piloting or implementing autonomous work capabilities report workforce reductions. However, these reductions do not appear to translate into a better return on investment. In fact, the survey found that workforce reduction rates were nearly equal between respondents who reported higher financial returns from autonomous technologies and those who experienced only modest gains or even negative outcomes.
Gartner surveyed 350 global business executives in the third quarter of 2025 to map these trends and understand the current state of autonomous work in enterprises. The study focused strictly on large companies; This means that each eligible organization reports annual revenue of at least $1 billion or the equivalent across the enterprise. Additionally, these companies were already piloting or fully implementing at least one of the three major developments involving AI agents, intelligent automation, or autonomous technologies. When businesses use tools such as AI agents, intelligent automation, robotic process automation, digital twins and tokenized assets, they are trying to push their operations towards true autonomy. This takes a company far beyond simple day-to-day automation. In a fully autonomous installation, both machines and humans operate with a much higher level of independence. Analysts emphasize that this change does not mean unmanned work, but rather human-assisted work.
Also Read | Standard Chartered plans to lay off thousands of people in its artificial intelligence move
“Many CEOs are turning to layoffs to demonstrate the rapid return of AI, but this attitude is misplaced,” said Gartner Distinguished Vice President Analyst Helen Poitevin. “Reducing the workforce may create budget space, but it doesn’t create returns. Organizations that increase return on investment are not organizations that eliminate the need for people, but organizations that empower people by aggressively investing more in the skills, roles, and operating models that enable them to drive and scale autonomous systems.”
The study states that autonomous business will create more jobs for people in the long run. This momentum is expected to accelerate further, as enterprise spending on AI agent software is certainly increasing rapidly. Gartner predicts that spending on this software will reach $206.5 billion in 2026, rising to $376.3 billion in 2027; That’s a huge jump from the $86.4 billion spent in 2025.
As autonomy for both software and humans will increase, the broad enterprise need for real humans will increase rather than decrease. As a result, Gartner predicts that autonomous businesses will become net-positive job creators from 2028 to 2029, a transformation driven entirely by new ways of working that AI cannot absorb.
Helen Poitevin has outlined the deep structural truths that will keep human talent at the very center of the modern enterprise. He noted: “Over the long term, autonomous business will create more jobs for people, not less. Persistent structural factors such as demographic decline and high-risk, trust-based consumer moments will ensure that human talent remains central to running, managing and scaling autonomous business.”
Facing the reality of the J curve
The Gartner research is echoed in another study recently published by the Stanford Digital Economy Lab. The report, titled ‘The Playbook for Enterprise AI’, takes a closer look at what happens when large companies try to implement automation. By tracking actual corporate outcomes, Stanford researchers explain why rapid layoffs fail to generate real profits.
One of the key takeaways from the Stanford playbook is a concept known as the productivity J-curve. This economic principle explains that when a company adopts a powerful new technology, its overall performance and profits often decline before rising. This initial decline occurs because real technological transformation requires massive, invisible investments. Companies can’t just buy software; They must spend heavily to reshape their daily workflows, rewrite corporate handbooks, and retrain their staff to use new tools effectively.
Because traditional corporate accounting cannot measure these hidden organizational costs, managers often miscalculate how long it will take to achieve a true financial return. Stanford research shows that new AI tools won’t scale if a company lays off workers without completely fixing and redesigning its internal processes. The highest financial returns are achieved when companies stop trying to replace human workers and instead create models in which people are specifically trained to handle complex exceptions and audit systems, while software performs standard tasks.
The job market resists the AI shock
While individual corporate leaders make headlines by cutting staff to fund technology budgets, broader economic data in the US shows that these layoffs are not devastating the broader job market. In a research note, ‘Artificial Intelligence Adoption and Firms’ Job Posting Behavior,’ published in March, economists at the Federal Reserve looked at the direct relationship between corporate automation and overall hiring trends. Using millions of real-world job postings, the central bank analyzed whether companies using heavy automation were actually closing their doors to human workers.
The findings from the Federal Reserve offer a reassuring reality check, consistent with Gartner’s optimistic long-term forecasts. The study clearly states that there is no evidence of an overall decline in job postings within industries or firms with high levels of AI adoption. While specific, highly repetitive jobs are certainly feeling the pinch from automation, forward-looking employers are offsetting these losses.
Automated companies dynamically change hiring priorities rather than reducing the total headcount. They are stepping back from routine data entry roles and actively seeking new staff to handle strategy, systems oversight and people-centered problem solving. The Federal Reserve emphasizes that the job market isn’t shrinking under the weight of new technology, it’s just rewriting the rules on who it should hire.
The human-powered future of corporate value
When you connect the dots between insights from Gartner, the Stanford Digital Economy Lab, and the Federal Reserve, the narrative around enterprise automation completely changes. Artificial intelligence is not simply a cost-cutting tool designed to replace the human workforce. Managers who view their employees as expendable liabilities seeking quick quarterly returns are actively harming their own long-term profitability.
Data from all these latest studies prove that the most successful and profitable companies are those that use new technology to enhance human capabilities rather than replace them. By leaving immediate budget pressures behind and investing heavily in a people-powered operating model, businesses can successfully navigate the initial challenges of adoption and create a lasting foundation for financial growth.
