Traditional planning, forecasting, and scenario models were built for environments with linear demand, stable unit economics, and predictable consumption. AI fundamentally breaks those assumptions.
As organizations adopt AI, FinOps teams are facing non-linear growth, volatile demand signals, and rapid feedback loops between product decisions and cloud cost — making traditional FP&A and scenario planning ineffective. The result is delayed visibility, misleading forecasts, and limited ability to intervene before spend accelerates. This session distills practical lessons from mature IT Financial Management (ITFM) practices and translates them directly into the FinOps context. Rather than introducing new tools or frameworks, it focuses on core finance and business practices that materially improve how FinOps teams plan, forecast, and respond to AI spend.
Attendees will leave with practical approaches they can apply immediately to improve forecasting accuracy, scenario thinking, and financial control for AI workloads.