Managing AI spending has become commonplace. Two years ago, 31 percent of organizations managed AI spending; today, 98 percent do.
This is according to research by the FinOps Foundation. It shows that FinOps has definitively shifted from pure cloud management to broad technology value management. AI cost management is now a top priority, while AI value management is the most sought-after skill within teams. Many organizations are tasked with financing AI investments themselves through efficiency gains, which directly links FinOps to strategic AI implementation.
The discipline now extends far beyond just the cloud. Nine out of ten professionals are being asked to manage SaaS, an increase of 65 percent last year. Licensing (64 percent, up from 49 percent), private cloud (57 percent, up from 39 percent), and data centers (48 percent) are also increasingly falling under FinOps.
Shift to executive level
FinOps teams are increasingly reporting directly to the CTO or CIO. 78 percent of teams now report to these executives, up 18 percent. Teams with VP/SVP/EVP/C-suite involvement show more influence on technology choices: cloud service selection (53 percent versus 24 percent), cloud provider selection (47 percent versus 16 percent), and cloud versus data center placement (28 percent versus 12 percent).
The role of FinOps leaders is expanding to include strategic vendor negotiations, commitment structures, and M&A technology research. They answer questions about ROI and value realization, not just savings. 28% of respondents indicate they manage or plan to manage labor costs within the FinOps practice.
Small teams with big impact
Notably, teams remain relatively small. 60 percent operate with centralized support via embedded team champions, with an additional 21 percent reporting hub-and-spoke models. Less than 10 percent report fully decentralized teams. Organizations managing more than $100 million have an average of 8 to 10 professionals and 3 to 10 contractors. They scale through enablement, AI productivity, and automation rather than headcount.
Shift left has become a top priority. Professionals are integrating financial context earlier in the engineering cycle, enabling teams to make informed decisions before deployment rather than having to remediate after the fact. Pre-deployment architecture guidance emerges as the most desired tooling capability.