Data center modernization unlocks AI budget headroom as enterprises fund new AI workloads
As enterprise AI budgets hit their limits earlier each year, the pressure to fund new agentic and inference workloads without expanding total spend is forcing a fundamental rethink of infrastructure and data center modernization.
The State of FinOps 2026 Report found that 98% of practitioners now manage AI spend, even as most organizations still overspend on AI workloads by four to five times their original budget. The core tension — more AI demand, constrained budgets, aging hardware — is exactly the problem Advanced Micro Devices Inc. says it is built to solve, according to Mike Thompson (pictured, right), director of cloud product at AMD and FinOps Foundation Project, a Series of LF Projects LLC, governing board member.
“The era of token maxing is kind of over because the spends are going through the roof,” Thompson said. “There’s a period of rationalization that I think the industry is going through now, particularly on AI applications and agentic [workloads], because those ones are really practical. … Budgets tend to get spent one to two quarters into the year. There’s so much dynamic development in the AI space that two to three quarters in, budgets are already tapped out.”
