FinOps AI governance demands new KPIs as token economics reshape enterprise cost models

FinOps AI governance is being stress-tested as AI spending accelerates across enterprises. The familiar levers of cost optimization — tagging, rightsizing and reserved capacity — are proving insufficient against a cost model governed by tokens, opaque billing and architectures that shift faster than governance frameworks can keep pace with.

The pressure is acute. According to the FinOps Foundation’s “State of FinOps 2026 Report,” 98% of practitioners now manage AI spend, up from just 31% two years ago — yet most organizations still lack the visibility and governance structures to control it at scale. That gap between adoption and accountability is what FinOps for AI must now close, according to Victoria Levy (pictured), senior staff FinOps analyst at SailPoint Technologies Inc.

“The [key performance indicators] are going to be way different,” she said. “We have tokens, so people are going to come up with your cost per token, maybe tokens per … whatever other business driver there is out there. It eventually will converge on things that are useful, and I think those will be part of the new foundation, and then we’ll be able to build off of that and start building our practices internally.”

Levy spoke with theCUBE’s John Furrier and Paul Nashawaty at FinOps X 2026, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how FinOps AI governance requires new models, cross-functional collaboration and outcome-based metrics to move beyond cost management into business value. (* Disclosure below.)

FinOps AI governance demands automation and cross-team collaboration

One of the clearest signals from the FinOps X floor was that automation is no longer optional. Without it, best practices erode the moment they are introduced, Levy noted. Enforcement — not just recommendation — is what makes gains stick.

“If you don’t have automation and you tell people to do some of the best practices and right-size, that’s only a one-time thing,” she said. “You need to implement that enforcement to make sure that the work you’ve already done stays there, and then you can build on it and go do different things.”

The danger of siloed decision-making is a recurring challenge in FinOps AI governance, Levy noted. AI billing today offers far less granularity than traditional cloud invoicing, making cross-functional context — between finance, engineering and security teams — essential to understanding whether a given cost represents waste or an intentional architectural trade-off, Levy noted.

“Everybody should be talking to everybody else, because there’s so much context about why your costs might be the way they are,” she said. “You might think that it’s not efficient, but they might have another reason, like a security requirement — so it’s not waste. Maybe it’s actually valuable. And so talking to them, you get that context to make better decisions.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of FinOps X 2026:

(* Disclosure: TheCUBE is a paid media partner for the FinOps X event. Neither the FinOps Foundation, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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