Tech leaders hoping AI might help save money and improve efficiency in IT infrastructure should know that only 28 percent of use cases fully succeed and offer return on investment (ROI).

According to new figures from Gartner, one in five AI projects in IT infrastructure and operations (I&O) fail outright.

Its survey of 782 I&O managers conducted in November and December last year found that 57 percent have suffered at least one failure in applying AI to their area.

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Melanie Freeze, research director at Gartner, said many AI initiatives flopped because of unrealistic expectations.

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"They assumed AI would immediately automate complex tasks, cut costs, or fix long‑standing operational issues," she said. "When expectations are not realistically set and the results don't appear quickly, confidence drops and projects stall."

"The 20 percent failure rate is largely driven by AI initiatives that are either overly ambitious or poorly scoped. AI that doesn't fit into the organization's operations simply can't deliver ROI."

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I&O leaders most frequently observe AI failures in auto-remediation, self-healing infrastructure, and agent-led management of workflows within and between systems, Gartner found.

Among I&O leaders who faced setbacks, 38 percent said persistent skill gaps continue to hamper AI success. The same proportion cited poor data quality or limited data availability as a direct cause of AI project failure.

The research found tech managers were more successful where the technology was more mature, such as applying GenAI to IT service management (ITSM) and cloud operations, with 53 percent of I&O leaders reporting success in those areas.

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However, there were challenges in getting funding for using AI in tech infrastructure "Many AI initiatives are still funded by individual business units, Freeze said. "However, as AI infrastructure spending continues to rise, CEOs and CFOs need to play a more active role in setting funding criteria and approving major investments."

The findings come against a backdrop of companies struggling to justify AI spending. In February, a survey of almost 6,000 corporate execs across the US, UK, Germany, and Australia found that [9]more than 80 percent detect no discernible impact from AI on either employment or productivity even though 69 percent of businesses currently use some form of AI.

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Another study from Harris Poll, commissioned by Dataiku, found tech leaders would come under pressure to show returns on AI investment in 2026: 98 percent said there was [11]increasing pressure from the board to demonstrate ROI , while 71 percent of the CIOs surveyed believed their AI budget would likely face cuts or a freeze if targets were not met by the end of the first half of the year. ®

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[5] https://www.theregister.com/2026/04/05/ai_agents_liability/

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[7] https://www.theregister.com/2026/03/19/pwc_ai/

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[11] https://www.theregister.com/2026/02/17/no_roi_no_ai/

[12] https://whitepapers.theregister.com/