How AI Agents can help scale FinOps practice

As a FinOps practitioner, I often find myself educating various personas within the organization on cloud bills, usage, and savings, among other topics. With each cloud provider offering over 100 cloud services and more than a million SKUs for purchase, it’s incredibly difficult for everyone to keep up with the complexity of cloud billing. Even with an open-source specification like FOCUS, which normalizes cloud datasets, the FOCUS v1.0 dataset contains 44 columns and millions of cloud billing records. Training thousands—if not millions—of professionals to learn a new taxonomy and vocabulary in cloud finance, while keeping up with constant changes, is a daunting challenge. Now, with a newly launched agent based AI services like Devin, we are introduced to an entirely new subscription model for software—beyond just a monthly subscription fee, organizations must now account for a resource called ‘Monthly Agent Compute Units.’ Cloud billing just became even more complex.

The Importance of a Decentralized FinOps Approach

One of the fundamental principles of FinOps is that ‘a centralized team drives FinOps.’ While that is important to jumpstart the FinOps practice in any organization, it is crucial to embed FinOps as a core capability and responsibility of every person who interacts with the cloud, either directly or indirectly. The more decentralized and pervasive FinOps becomes, the more value an organization can extract from its cloud investments.

The Role of AI Agents in Scaling FinOps

The State of FinOps 2025 Report suggests that the FinOps practitioners are expected to increase their effort in 12 core capabilities besides manage additional scope of technology spend that includes SaaS, Licensing, private cloud and data centre. Central FinOps teams are usually 5-10 member strong and will be stretched to deliver advanced FinOps capabilities across all these technology domains. AI agents will be at the forefront of driving FinOps at the edge of the organization by focusing on three key areas:

1. Autonomous Cloud Optimization: AI-driven tools such as Sedai.ai and Cast.ai can autonomously optimize cloud environments to ensure savings particularly on low-return-on-investment (ROI) recommendations generated by numerous tools. It’s clearly not worth your engineer’s time to save $50 on an unattached EBS volume but it sure is worth an AI Agent’s time to do just that.
2. Make Cloud easy to understand: AI agents can process millions of rows in cloud billing files, observability logs, software usage reports, Human Capital Management (HCM) systems, and Enterprise Resource Planning (ERP) platforms to quantify and articulate the true value of cloud investments for executives. This capability enables organizations to build more confident and data-driven cloud strategies. With advanced document processing and comprehension features, AI Agents can very easily support a Finance lead perform a standard task like approving a cloud business case to a CTO perform a complex task like presenting a data-driven strategy for digital transformation that builds on the learning from past cloud deployments within the organization and best practices elsewhere
3. Render a FinOps assistant for every persona: AI agents will drive productivity by handling FinOps-related requirements for a variety of roles, including software developers, solution architects, IT operations professionals, finance managers, technology project managers, IT procurement specialists, and more. These agents will help organizations retain the FInOps knowledge base through periods of change with vendors, managed service providers, SaaS providers, and their very own knowledge workers.

A Real-World AI in FinOps Customer Story could look like this

Consider Haven & Home (H&H), a $1B omnichannel furniture retailer which is leveraging Agentic AI to optimize its FinOps strategy. With increasing technology costs, declining margins, and rising competition, H&H's CFO aims to improve profitability and efficiency while maintaining growth.

AI-driven FinOps solutions can help H&H in several ways:

1. Technology Budget Control – AI agents analyze ROI, eliminate redundant software, predict cost overruns, and optimize SaaS spending.
2. Finance & Procurement Automation – AI centralizes financial operations, standardised processes, provides real-time insights, and automates vendor negotiations.
3. Productivity Enhancements – AI automates invoice reconciliation, fraud detection, and financial benchmarking, reducing manual work.

By integrating Agentic AI, H&H anticipates a 5% margin improvement, 15-20% cost reduction, 2% market share growth, and enhanced cash flow. AI’s automation and insights will drive strategic financial decisions, boost efficiency, and create a resilient, customer-focused business.

Join the Conversation

If you’re as excited as I am about the explosive impact AI will have on FinOps, I’d love to connect over a coffee chat! Let’s explore how AI can revolutionize financial operations and cloud cost management in your organization.

Bio:

Arvind Shastry is a certified FinOps Practitioner and leads the FinOps practice at Transport for NSW based in Sydney. He has 15+ years of experience as a Business Strategy and Operations expert across organizations such as Tata Group, InMobi and Amazon. He is also a FinOps content creator and a member of the FinOps Foundation.