Just 22% of organisations have successfully scaled AI across multiple business units or adopted an AI-first approach, despite investment in the technology continuing to accelerate, according to Gartner.
The analyst’s survey of 1,303 respondents found 85% of functional leaders plan to increase AI spending during 2026, having already allocated an average of 12% of their functional budgets to the technology in 2025.
However, visibility over that investment remains a concern. Around 11% of organisations were entirely unaware of how much their function spent on AI last year.
Tina Nunno, Distinguished Vice President and Gartner Fellow, warned that the lack of financial visibility creates additional risk as investment increases.
“Without disciplined measurement tied directly to business outcomes, organisations risk wasted resources and unmet expectations,” she said.
Gartner found organisations continuously tracking return on investment performed significantly better. High-performing businesses reported positive returns from 81% of their AI initiatives, while low performers did not know the return generated by 29% of their projects.
Productivity remains the dominant objective, targeted by 75% of functional leaders and accounting for approximately 30% of functional AI spending.
Popular IT use cases not necessarily delivering best returns
The research also identified a disconnect between the AI applications IT leaders are pursuing most frequently and those generating the strongest reported returns.
Cybersecurity threat detection and response and IT service desk automation were each being pursued by 54% of C-suite leaders, while 44% were investing in automated code generation and refactoring.
However, intelligent IT asset and cost optimisation was the use case most commonly associated with positive returns, cited by 40%. This was followed by synthetic data generation at 28% and automated code generation and refactoring at 23%.
“Organisations are seeing the greatest quantifiable value from less common, strategically selected use cases that are closely aligned to their unique business needs,” Nunno said.
For CIOs and cybersecurity leaders, the findings suggest that rapidly expanding AI portfolios without corresponding governance and financial oversight could create unnecessary cost and complexity.
Rather than pursuing high-profile applications simply because competitors are adopting them, Gartner argues organisations should connect individual AI investments to clearly defined outcomes, continuously measure performance and be prepared to reallocate funding or discontinue initiatives that fail to deliver.
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