FinOps for AI and Data Workloads: Why Dashboards Are No Longer Enough for Cloud Cost Control

Discover how enterprises must evolve their FinOps strategy to manage AI and data workload costs in real time. Industry experts Vijay Prankumar and Kiran Jain (CEO of Finopsly) break down the accountability gap, shadow AI spend, governed automation, and the steps leaders must take to connect cloud and AI costs to real business value.

Timestamps

00:00 - Intro & Guest Overview
01:00 - The Strategy Gap in Cloud & AI Spend
02:25 - Budget Accountability & Planning Cycle Challenges
03:20 - Engineering vs Finance in FinOps Structure
04:15 - How AI & Data Workloads Changed FinOps
05:30 - The Monthly Billing Cycle Is No Longer Enough
06:45 - Shadow AI: The New Unmanaged Spend Category
07:45 - Attribution & Tagging AI Costs Across Stacks
08:30 - Where Is FinOps Heading in the Next 12 Months?
09:40 - Shadow AI Spend: A Real Enterprise Problem
11:00 - DBUs, Snowflake Credits & Unified Cost Metrics
12:30 - Bridging Finance & Engineering with a Common Language
13:30 - Real-Life $60K Snowflake Query Gone Wrong
16:00 - The Need for Real-Time Anomaly Detection
18:30 - C-Level ROI Pressure & AI Spend Governance
21:00 - Governance vs Dashboards: A Critical Distinction
23:00 - Value Control as the Next FinOps Frontier
26:00 - What Separates Successful FinOps Organizations
31:30 - Governed Automation in Regulated Industries
35:30 - 3 Actionable Steps for Leaders to Fix FinOps
38:30 - One Key Piece of Advice to Make FinOps Work
41:00 - Final Thoughts & Wrap-Up