AI is reshaping how cloud infrastructure is built, deployed and consumed — and FinOps practice needs to keep pace. The scale and speed of AI-driven infrastructure demands a smarter, more autonomous approach — one that creates a consistent governance experience across FinOps leaders and engineering teams, speaking to both cost accountability and operational velocity. In this session, we share a real-world experience of evolving FinOps from foundational policy and governance, through automated guardrails, to the next frontier: Agentic AI.
Imagine an AI agent watching as a developer writes infrastructure code — flagging cost and compliance issues in real time, before a pull request is even raised, or surfacing utilization issues as they happen across your cloud and AI infrastructure. And when agents act autonomously, a dedicated FinOps agent tracks every action taken, every dollar saved, and every policy enforced. In short — fighting the complexity of AI with the intelligence of AI.
You’ll leave with a practical understanding of:
- How to build a governance experience for FinOps leaders and engineers that spans cloud infrastructure and AI services — from compute and storage to foundation models, inference endpoints, and training workloads — using a Discover, Fix, Prevent model powered by policy-as-code and Agentic AI.
- From Intent to Policy — how developers and FinOps leaders can use Agentic AI to describe a governance intent in plain language and have it automatically translated into enforced policy — self-service governance at the speed of conversation
- Shift-Left FinOps — as AI coding assistants accelerate infrastructure development, AI agents can now scan code and infrastructure-as-code at the pull request stage — catching cost and compliance issues at the source, before they reach production or land on the bill
- How Agentic AI and MCP servers are changing what’s possible — reasoning and acting across your entire stack and multiple MCP servers managing cloud infrastructure
- Governing and Measuring Agentic AI Value for FinOps — from cost savings identified and policies enforced, to pull requests flagged and reports generated — know exactly what your agents and engineers are doing and the value they are delivering
