Flexera has released the Flexera 2026 State of ITAM Report, highlighting a widening gap between the rapid adoption of AI and organizations’ ability to effectively manage it. Although nearly half of organizations now track AI as part of their software spending, only 31% say they have accurate visibility into their AI software assets. At the same time, 59% of respondents say wasted AI spend has increased year over year, highlighting rising cost pressures as enterprises adopt AI at scale and it becomes a core spending category.
“AI is changing the economics of IT faster than most organizations can adapt,” said Becky Trevino, chief product officer, Flexera. “What we’re seeing is a familiar pattern of rapid adoption followed by a scramble for visibility and control. The organizations that succeed will be those that bring AI into the same governance and optimization frameworks they’ve built for on-premises, SaaS and cloud.”
Key findings from the latest Flexera 2026 State of ITAM Report include:
- Technology visibility is declining: Complete IT asset visibility dropped to 36%, reflecting growing complexity across AI, SaaS and cloud environments.
- Audit activity remains high and costly: Nearly half (48%) were audited in the last year and only slightly less (44%) report spending over $1 million on software audits over the past three years, a figure that has stayed stagnant for the past three reports.
- Microsoft continues to drive audit activity: 64% of respondents said Microsoft audited their organization in the past three years, continuing to remain at the top of the list for the past several reports. In a big fluctuation, Oracle made a notable jump to the top three, having increased to 38% from 24% the previous year. Adobe also made a change from 24% to 32%.
- ITAM and FinOps collaboration shows signs of strain: Interaction between teams has declined year over year, even as organizations increasingly rely on both groups to achieve comprehensive visibility.
- Cost optimization leads IT priorities: ITAM teams spend the largest share of their time on software optimization (32%), followed by audit response (22%) and allocation (22%).
This year’s data reflects a broader shift, as AI spans existing technology categories across cloud, SaaS, data centers and devices while introducing entirely new layers including models, agents, data and platforms, governed by new economics. Layered onto already complex environments, this expansion is accelerating existing cost and visibility challenges. As organizations scale AI initiatives, they increasingly need unified visibility across software, cloud and AI to control spend and reduce risk.
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