Three insights you may have missed from theCUBE’s coverage of FinOps X 2026
AI costs are becoming one of the most difficult aspects of enterprise AI adoption.
Unlike traditional cloud or software-as-a-service spend, AI costs are shaped by dynamic usage patterns, model behavior and external interactions, making it harder to keep investments aligned with business value. As enterprise AI adoption grows, organizations are reevaluating traditional cost governance models, according to Marco Meinardi, vice president analyst at Gartner Inc.
“With AI, now we’re dealing with spending sources that are even outside of our organization, and I’m not just talking about agents that have potentially endless loops of reasoning,” he said in an interview. “We’re also dealing with end users, our customers … and how they use our AI application — how they prompt them — is going to influence our costs. We’re dealing with two different problems that will require different solutions.”
Meinardi spoke with theCUBE’s John Furrier and Paul Nashawaty at FinOps X 2026, during an exclusive broadcast on theCUBE, SiliconANGLE’s livestreaming studio. FinOps leaders gathered at the event to discuss the growing challenges of AI cost governance and the need for new frameworks to measure, govern and manage AI costs as adoption accelerates. (* Disclosure below.)
