Datadog’s FinOps analyst says AI cost management starts with tagging and model governance
AI cost management is bringing a new taxonomy to FinOps practitioners, but the core discipline, understanding what you’re using, why, and what it costs, remains the same.
That constancy is reassuring and instructive, according to Deeja Cruz (pictured), senior FinOps analyst at Datadog Inc. The biggest practical lesson enterprises can carry from cloud to AI is to maintain high-quality attribution tags. Without them, the ability to allocate spend and identify optimization opportunities collapses, regardless of how sophisticated the AI workload is.
“The biggest takeaway that I can give is don’t neglect your tags,” Cruz said. “Having good tagging on your data will unlock your ability to allocate it and be able to answer questions that executives are asking.”
Cruz spoke with theCUBE’s John Furrier and Paul Nashawaty, principal analyst at theCUBE Research, at FinOps X 2026 during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how AI cost management is developing the FinOps role and how collaboration throughout engineering, finance and security appears in practice. (* Disclosure below.)
