OpenAI CFO Sarah Friar shares five lessons for building an AI-native finance function, aiming for a zero-day close and continuous forecasting. When Friar joined OpenAI two years ago, the growing company needed to build its finance function from the ground up, moving away from manual tasks like finding information and assembling spreadsheets. To redesign finance around advanced AI tools, OpenAI paired broad employee access with structured experimentation. For example, a finance hackathon brought sales engineers together to build custom GPTs for investor relations, procurement, and tax. Friar stresses that CFOs need both bottom-up experimentation and top-down strategy. By working backward from consequential decisions, finance teams can map out data and approvals to let AI handle initial explanations and flag exceptions, while finance retains ownership of the final sign-off. Furthermore, OpenAI research indicates that finance professionals are using AI for tasks outside traditional finance, with team members building live dashboards and tools using ChatGPT Work and Codex rather than relying solely on static Excel models. This shift allows finance professionals who understand the problem to directly shape the technological solution.
What building an AI-native finance function taught me
OpenAI CFO Sarah Friar outlines lessons learned from building the company's AI-native finance function over the past two years. The approach focuses on achieving a zero-day close and automated, continuously updated forecasting. Friar emphasizes that integrating AI requires combining bottom-up experimentation with top-down strategy.
Why it matters
This article demonstrates how tech companies are actively replacing traditional spreadsheets with AI-driven, real-time financial tools, signaling a broader shift in enterprise software use.
Topic dossiers OpenAI