The findings point to a problem for businesses moving from AI experiments into production. Adoption keeps accelerating, but many organisations find AI costs hard to predict and control. Of the respondents, 45% said they have moved AI workloads or projects because of cost volatility, a trend that echoes last year's report, which named cost as the biggest barrier to successful AI implementation.
Spending is still rising. More than half of respondents (55%) increased their AI investment in the past year, yet returns are hard to show: 58% said the value their AI initiatives generate is roughly equal to their cost, 23% said AI delivers more value than it costs, and 27% reported little to no measurable impact.
Data sovereignty is also shaping deployments. 84% of organisations said residency or jurisdiction-specific requirements influence where they run AI workloads, which points to a need for flexibility and control over infrastructure.
Visibility is improving but precision lags. Nine in ten respondents said they can measure how much they spend on AI from start to finish, but only 27% can do so very accurately.
David Brown, Solutions Director at AND Digital, commented on the findings: “As AI adoption accelerates, token costs are becoming a significant challenge for businesses looking to scale their AI investments and understand ROI and efficiencies gained.”
To stay across the latest in cloud, AI and enterprise tech analysis from Compare the Cloud, subscribe to our weekly newsletter at https://www.comparethecloud.net/newsletter
