in short:
Flexera’s 2026 State of ITAM report shows that ITAM teams are entering a new era of the technology economy in which cloud, SaaS and AI costs are more difficult to see, predict and manage. The opportunity for practitioners is not to become an AI cost expert overnight, but to build new skills and develop stronger partnerships with FinOps, increase visibility, and begin to tie technology spend to measurable business value.
If you work in IT asset management, the past few years may have felt like a long-term expansion of your job description. The first is cloud computing, with its ever-changing targets and costs based on consumption. The SaaS purchase then spreads throughout the enterprise, often faster than the team can track it. Now, AI brings another layer of complexity: usage is harder to see, harder to predict, and harder to tie to business value.
Flexera’s 2026 State of ITAM report shows how quickly things are changing. 84% of organizations now see AI adoption and tracking as a top challenge, but only 31% understand AI software. At the same time, 59% of respondents said wasteful AI spending is increasing. This is the core question facing ITAM teams today. Artificial intelligence is being adopted faster than governance. For the first time, even visibility struggled to keep up. This means ITAM teams need to manage rapidly growing areas of spend that many organizations still don’t fully understand.
For ITAM leaders wondering how to become an AI economist overnight, there are some practical ways to move forward while the market, pricing models, and measurement frameworks are still taking shape. But the first step is recognizing that this role must evolve from its traditional role.
How cloud, SaaS and AI are expanding the role of ITAM
The report makes it clear that ITAM’s responsibilities have expanded. Three-quarters of ITAM teams now manage cloud software licenses. 64% manage SaaS. More than half are already responsible for visibility into AI spending. Meanwhile, nearly 80% of organizations have a dedicated FinOps function.
This creates a new reality. Traditional software licensing provides teams with relatively specific things to work on: contracts, entitlements, deployments, renewals, and audit exposure. Cloud and SaaS make this process more difficult by introducing variable consumption and decentralized purchasing.
Artificial intelligence adds another transformation. Costs may be related to users, models, tokens, tips, workloads, agents, integrations, or results. In many cases, businesses may experiment before there are proven ways to measure whether the use is effective or worthwhile. The challenge is that most practitioners have not yet received formal training for this expanded role. In a world where costs are dynamic, consumption-based and tied to real-time usage, traditional ITAM frameworks alone are not enough. ITAM has always been about creating control out of complexity. This hasn’t changed. What has changed is the type of complexity that practitioners are asked to manage.
Why ITAM professionals must upskill now
The most pressing task for ITAM professionals is to expand their capabilities beyond traditional asset management. As the Flexera data cited above shows, ITAM teams are responsible for AI spending but don’t know what that spending is. This gap is why skills like FinOps, AI cost governance, and consumption-based optimization become critical.
FinOps is a great place to start.
FinOps brings a different operating model. It focuses on continuous optimization, shared responsibility and real-time decision-making. These are exactly the capabilities needed to manage cloud and AI environments. For ITAM practitioners, this means moving from periodic license optimization to ongoing consumption management. Understanding the core principles of financial operations and seeking formal certification will soon become table stakes, not optional. In the meantime, practitioners should pay close attention to emerging frameworks that address issues that FinOps does not yet fully address.
Artificial intelligence introduces a new dimension: value.
It’s no longer enough to just know how much something costs. Organizations need to understand what this cost will entail. This is where token economics start to become important. Token-based pricing models, cost per interaction and cost per outcome will define how AI is governed in the coming years. The work being done by the Tokenomics Foundation is an early signal of how the field is developing, and ITAM professionals should actively track these developments.
Why ITAM and FinOps should align around technology economics
One of the most practical steps organizations can take is to formalize collaboration between ITAM and FinOps. In many cases, both features already exist. They just operate in parallel. The opportunity is to bring them together into a unified techno-economic group. The group’s purpose should be simple: create a single model to manage the cost, consumption, and value of the entire IT estate. In practice, the group will focus on a number of key outcomes.
- Establish clear cost ownership across cloud, SaaS and AI. The report shows that responsibility for software savings in the cloud is now split almost equally between ITAM and FinOps. Without coordination, confusion and gaps can result.
- Define consistent metrics. This includes not only total spend, but also unit economics such as cost per user, cost per workload and ultimately cost per AI interaction.
- Drive visibility. The organization’s full visibility has dropped to just 36%, highlighting how much work still needs to be done.
- Coordinate optimization efforts. Today, optimization is often fragmented. The technical economics group can create a single backlog of optimization opportunities across vendors, platforms, and environments.
Quick results for improved ITAM and FinOps alignment
This doesn’t require years of transformation to begin. There are some practical steps ITAM and FinOps teams can take immediately.
- Start by creating a joint forum between ITAM and FinOps leaders. Even a monthly work meeting focused on shared priorities can start to break down barriers.
- Coordinate a small number of shared metrics. For example, focusing on software waste, license utilization, and cloud cost efficiency can create a common language among teams.
- Target specific vendors or spend categories. Microsoft, Oracle, or SaaS applications are often a good starting point. Demonstrating measurable savings in one area can quickly build credibility.
- Start bringing AI into governance discussions now, Even if the visibility is incomplete. Waiting until it’s fully visible will only delay progress.
How ITAM drives executive alignment on technology spending
The final part is performing the adjustments. ITAM is at an inflection point because cost pressures are no longer isolated to IT. Now it has become a board-level concern.
Leaders are not asking for better tools. They demand better results. This creates an opportunity for ITAM to reposition itself.
The conversation should move away from compliance and audits and toward value, efficiency, and control of technology spend.
Executives responded to the clear narrative:
- Where do we spend our money?
- Where are we wasting?
- Where can we optimize?
- How do we govern new fields like artificial intelligence before they scale?
A unified techno-economic model powered by ITAM and FinOps provides direct answers to these questions.
The future of ITAM is techno-economic
ITAM is not being replaced, but it is being redefined. The core disciplines remain important, but the scope has expanded beyond recognition. Managing assets is no longer enough. Consumption now needs to be managed. Next is management value. Successful organizations will be those that adapt early.
For practitioners, this means developing new skills, embracing FinOps, tracking emerging token economic frameworks, and actively shaping how these disciplines converge. The opportunity is significant.
For the first time, ITAM is positioned not just as a control function but as a central player in the economics of managing technology at scale for organizations.
Next step: If your organization is trying to control cloud, SaaS or AI-related spending, talk to an SHI expert. SHI can help you bring ITAM and FinOps together to form a more practical operating model.
Want to learn more about this topic? Read our blog on AI FinOps – How to stop chasing tokens and start measuring results
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