For years, ITAM (IT Asset Management) teams' jobs were straightforward: track technology assets, maintain compliance, and optimize software investments. Today, those boundaries have blurred. As organizations navigate increasingly complex technology environments alongside the rapid rise of AI, ITAM has evolved from an operational function into a strategic discipline that helps organizations govern technology across the enterprise. The question facing organizations is no longer how to manage technology assets, but who should own them.

As AI becomes increasingly embedded across every business function, traditional ownership models are breaking down. Cloud software assets increasingly overlap with FinOps. AI adoption involves security, procurement, legal and business leaders. Employees are adopting new AI capabilities faster than governance models can keep pace. The result is a growing need for greater visibility, clearer accountability, and stronger collaboration across teams.

AI Is Creating a New Visibility Challenge

There's no denying the pressure organizations feel to adopt AI. Generative AI has reached 53% adoption in three years, faster than the personal computer or internet, according to Stanford HAI.  

Yet despite its rapid rise in popularity, many organizations and their employees are adopting AI before any formal approval or governance processes are in place, creating one of the greatest challenges for ITAM today: visibility.

Organizations increasingly need to understand which AI tools are being used, who is responsible for them, what they cost, and whether they are delivering measurable business value. According to Flexera's 2026 State of ITAM Report, 84% of organizations cite tracking and adopting new AI applications as the top combined challenge overall. At the same time, only 31% report accurate visibility into their AI software.

Without clear visibility, organizations will continue struggling to answer fundamental questions about AI spend and ROI. As AI becomes embedded across the enterprise, organizations need governance models built around shared ownership. No single team has complete visibility into AI usage, cost, risk and value. Effective governance requires security, FinOps, engineering, procurement, and business stakeholders to contribute their own perspectives and data. ITAM plays an important role in that model by helping establish the visibility and governance foundation that supports informed decision-making across teams.

But visibility alone doesn't solve the ownership challenge. Once organizations understand what AI is being used, they must also determine who is responsible for governing it.

The Rise of Cross-Functional Collaboration

AI is only accelerating a broader trend that has been reshaping ITAM for years: the convergence of technology management disciplines. As organizations face growing complexity across cloud, SaaS, and AI environments, teams are moving away from siloed ownership models and toward shared accountability.

The report highlights how this shift is well underway. Nearly all ITAM professionals report at least some responsibilities related to FinOps, while 75% are responsible for cloud software license management. In addition, among SAM teams that report into cybersecurity, 58% track AI usage, and HAM responsibilities also increased, with maintaining accurate inventories remaining a central focus.

Each of these functions brings unique expertise and visibility into technology investments. As ITAM, SAM, HAM, engineering and FinOps' responsibilities continue to converge, collaboration becomes the mechanism that connects data, decisions, and execution across teams – turning fragmented insights into a unified approach for maximizing technology ROI.

The answer, then, isn't that ITAM owns AI outright. It's that effective AI governance depends on coordinated decision-making across FinOps, security, procurement and business stakeholders and ITAM teams, with each contributing a different perspective about technology usage, risk and spend.

MSPs Emerge as Strategic Governance Partners

Growing technology complexity is also changing how organizations use managed service providers (MSPs) as part of their ITAM strategy. The report found that 75% of organizations use MSPs for ITAM needs, with larger organizations and those with more ITAM FTEs more likely to rely on them. 
As governance responsibilities continue to expand beyond what many internal teams can support alone, organizations may work with MSPs to augment their expertise and operational capacity.
As SaaS, cloud and AI continue to expand, maintaining accurate software records, understanding licensing obligations and preparing for audits has become significantly more challenging. The report found that nearly half of organizations (48%) received a software audit in the past year, while 44% reported spending more than $1 million on software vendor audits over the past three years.

Rather than replacing internal ITAM teams, MSPs are increasingly helping organizations extend their governance capabilities. They provide specialized expertise in software licensing, data management, audit readiness and operational execution, allowing internal teams to focus on higher-value governance, optimization and strategic decision-making.

The Future of ITAM Is Shared Governance

The rise of AI, expanding technology environments, and increasing complexity across the enterprise have fundamentally changed what organizations need from ITAM.

Success is no longer measured by simply maintaining accurate inventories or ensuring software compliance, but by how effectively organizations can lower costs, improve visibility, manage risk, and make informed business decisions across increasingly complex environments. Governance has become the common thread connecting technology ownership, financial accountability and business value.

It's time to say goodbye to the "traditional ITAM" era. Looking ahead, successful ITAM programs will be those that embrace shared ownership across ITAM, FinOps, security and procurement while improving visibility into AI usage and leveraging trusted partners where additional expertise is needed.

So, who really owns AI? Increasingly, the answer is no single team.

AI governance depends on a shared model in which ITAM, FinOps, security, procurement and business stakeholders each own part of the process. ITAM's role is to provide the visibility, data discipline and governance foundation that helps those teams act from a common view of technology usage, cost and risk. As AI becomes a permanent part of the technology estate, organizations that establish these foundations now will be better positioned to control spend, reduce risk and maximize the value of every technology investment.