The bottom line: Only one-third of IT asset management teams can reliably account for costs and benefits of AI projects, while over 50 percent report AI spending without measurable added value.
According to Flexera’s State of ITAM Report 2026, enterprises are investing massively in AI solutions but rarely have transparent cost tracking and governance processes in place. This leads to budget overruns and difficult-to-measure return on investment.
The Flexera State of ITAM Report 2026 documents a systematic problem in AI management: While AI becomes a priority IT investment for enterprises, AI spending is typically not tracked separately but allocated to existing software budgets. This significantly hinders the assessment of economic benefits and makes it nearly impossible to determine the return on investment of AI projects.
Approximately half of surveyed enterprises track the use of AI applications and adjust contracts accordingly. However, only about one-third of IT asset management teams have reliable data on actual costs. Over 50 percent of IT leaders report rising AI spending for solutions without measurable added value – including unused licenses, oversized models, or pilot projects that never went into production.
Complexity is growing because AI is no longer an isolated technology but permeates cloud platforms, SaaS solutions, data centers, and end devices. New layers such as AI models, agent systems, and specialized data platforms are emerging in parallel. Only 36 percent of enterprises report comprehensive visibility of their entire IT assets – a notable decline in transparency.
In parallel, IT asset management is significantly burdened by software audits: Almost one-quarter of IT-AM teams’ working time goes into internal and external audits. Nearly every second enterprise was audited by software vendors in the past year, particularly by Microsoft, Oracle, and SAP in Europe. 44 percent of enterprises spent more than one million US dollars on software audits and resulting measures over the past three years.
For CDOs, the strategic requirement is clear: AI must be integrated into established governance, cost, and optimization processes – not retroactively, but from the start. The pattern repeats with every new technology: speed initially trumps control, later transparency and structure become expensive to implement afterward.
Source: www.it-daily.net · Published 30 June 2026
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