FinOps discipline finds its footing in managing AI spend as token economics reshape enterprise budgets
As generative AI accelerates from a product experiment into a core enterprise operating cost, the discipline of FinOps is evolving rapidly around managing AI spend, introducing a layer of complexity that traditional cloud budgets never fully prepared practitioners to handle.
Token economics are forcing organizations to rethink not just how they measure spend, but what costs even count — from inference and database throughput to developer hardware and workforce transformation. That convergence of AI and financial operations is putting FinOps teams at the center of decisions they were not originally chartered to make, according to Jennifer Hays (pictured, left), senior vice president and head of engineering excellence and technology strategy execution at Fidelity Investments.
“You have to get transparency in your token costs,” Hays said, “but you have to understand actually how it impacts probably a dozen or more costs around you. There’s a whole segment of costs that come with it — what is going to happen with your input, your output into your large databases, your Snowflakes and those types of things. Even laptops for your developers — are you going to think about running models locally?”
