FinOps, evolving into an essential operational model for the AI era

FinOps has now surpassed the cloud cost optimization field to become a key element in managing the value of technologies such as AI. The latest “FinOps 2026 Report” shows that 98% of respondents are managing AI expenses, and 90% also cover SaaS management. Additionally, through collaboration with management, FinOps practitioners’ influence on technology selection decisions has increased two to four times.

Recent analysis by theCUBE Research indicates that more organizations are adopting the FinOps Open Cost and Usage Standardization (FOCUS) to standardize multi-source billing data and leverage AI-driven insights. The analysis emphasizes that FOCUS standardization and collaboration with management signal a future trend where financial intelligence will stand alongside observability and security. “FinOps is no longer just a cost reporting function but has evolved into an operational model for technological value in the AI era,” Nashawaty and Weston explain.

In the software development lifecycle, the trend of integrating financial considerations into infrastructure preparation and AI workload deployment continues to deepen. This involves proactively assessing costs related to cloud region selection, data residency strategies, and more, enabling smarter financial decisions. Consequently, developer incentives and investment return distribution mechanisms are becoming increasingly complex.

A recurring theme throughout the report is the integration of AIOps and FinOps. As AI-driven FinOps becomes a priority for enterprises, its importance in machine learning conversations is growing. While AI exacerbates infrastructure complexity and cost volatility, FinOps effectively manages these expenses. AI also continuously enhances FinOps operational efficiency through prediction, anomaly detection, and automated cost allocation.