Flexera 2026 State of ITAM Report: How leaders are balancing AI cost optimisation and governance
Flexera 2026 State of ITAM Report: How leaders are balancing AI cost optimisation and governance
AI is reshaping ITAM faster than any previous technology shift - but that doesn't mean the fundamentals of good ITAM have changed.
Published on 2nd July 2026
Flexera’s newly-released 2026 State of ITAM Report reveals a growing disconnect: Organisations are investing heavily in AI tools, yet many lack the visibility and governance needed to manage them effectively. This tension creates a new challenge, and IT leaders are asking themselves:
How do we govern AI usage without slowing innovation and limiting ROI?
Below, is a breakdown of the key AI-specific findings shaping enterprise ITAM strategies today.
AI adoption is accelerating—but only 31% of organisations report having visibility into AI software
AI has rapidly moved from experimentation to a core part of the IT estate.
- AI tools have surged in importance, rising from 1.94 to 3.13 on a 5-point technology relevance scale in just one year
- 47% of organisations plan to significantly increase their focus on AI software
- Only 36% report complete visibility across their IT estate, a year-over-year decline
At the same time, 84% of respondents highlight AI tracking as a top challenge. AI is expanding faster than traditional asset management models can support. Without visibility into AI tools being used, organisations risk operating with blind spots across cost, usage and risk.
Only 32% of organisations track AI applications within their configuration management database (CMDB)
AI governance is struggling to keep pace with adoption. As AI usage grows, governance gaps are becoming more visible.
- 45% are actively identifying unsanctioned or shadow AI usage
- 58% of SAM teams tracking AI report into cybersecurity teams, signalling a shift toward security-driven oversight
- AI tracking is now the top planned ITAM responsibility at 47%
AI governance today is largely reactive. Most organisations are trying to catch up with adoption rather than controlling it upfront. Governance models are often built after AI is already embedded across the environment.
AI cost management is emerging as a critical challenge: 59% of organisations report increased wasted AI spend
AI doesn’t just add more tools. It changes how tools behave, and that’s why AI makes SaaS sprawl harder to control. AI-enabled SaaS often:
- AI-related spend tracking is now bundled into broader software spend management for many organisations
- More than half of ITAM teams already support AI spend visibility responsibilities
AI cost management is still immature. Rapid experimentation and decentralised adoption are driving inefficiency before optimisation frameworks are fully in place.
With only 29% of organisations measuring the value of AI software, determining ROI is still in early stages
While investment in AI continues to grow, value realisation remains limited.
- According to survey respondents, AI tools aren’t yet delivering strong savings outcomes compared with SaaS or cloud optimisation
- 48% of organisations are already tracking and rightsizing AI contracts
Organisations are starting to apply traditional optimisation practices to AI, but ROI frameworks are still catching up. The challenge isn’t just controlling cost—it’s proving business value.
AI usage governance is becoming a shared responsibility
AI is accelerating the convergence of ITAM, FinOps and security teams.
- 51% of ITAM teams support AI spend visibility
- AI governance responsibilities now span IT, security and financial teams
- Many organisations split accountability for optimisation and cost control across functions
Governing AI usage is no longer owned by a single function; it requires cross-team coordination between ITAM and FinOps. That adds complexity, but it also creates an opportunity for stronger control and clearer accountability.
The core challenge: governing AI without limiting innovation
- Too much governance creates friction
- Too little governance creates risk and waste
Today, many organisations lean toward fast adoption followed by delayed governance.
How leading organisations are closing the gap between increasing governance without delaying AI’s output
While the report highlights real challenges, it also shows where organisations are focusing next.
- Expanding AI visibility across tools and environments
- Integrating AI tracking into existing ITAM and CMDB systems
- Applying cost optimisation practices such as rightsizing and contract management to AI
- Strengthening alignment between ITAM, FinOps and security teams
The goal isn’t to slow AI adoption. It’s to make AI measurable, governable and accountable.
Final takeaway
AI is reshaping ITAM faster than any previous technology shift. But the fundamentals haven’t changed. The organisations that succeed will treat AI not as a standalone experiment, but as a managed, measurable part of the IT estate.
Get the full picture
See how your AI governance and cost optimisation stacks up against other organisations in Flexera’s 2026 State of ITAM Report.
Read the full reportSource
Image Credit
Flexera