What building an AI-native finance function taught me
OpenAI’s CFO outlines five key strategies for transforming finance functions with AI, emphasizing automation, forecasting, and ROI tracking.
- Automating routine finance tasks like forecasting and reporting can significantly improve efficiency and allow teams to focus on strategic work.
- Stronger internal controls are essential to mitigate risks introduced by AI systems in financial operations.
- Measuring AI’s ROI in finance requires updated metrics to capture efficiency gains and cost reductions.
- Finance functions are emerging as early adopters of AI, setting trends for broader enterprise automation.
Sarah Friar, Chief Financial Officer at OpenAI, shares practical insights from her experience building an AI-native finance function. She highlights five core lessons, including the automation of routine tasks like forecasting and reporting, which free up teams to focus on strategic analysis. Friar also emphasizes the importance of stronger internal controls to manage risks introduced by AI systems, ensuring compliance and reliability in financial operations.
Another key takeaway is the focus on measuring AI’s return on investment (ROI) in finance. Friar argues that traditional finance metrics must evolve to account for the efficiency gains and cost reductions enabled by AI tools. This shift not only improves operational performance but also aligns finance teams more closely with broader business objectives.
The lessons reflect broader trends in enterprise AI adoption, where finance functions are increasingly seen as early adopters of automation and predictive analytics. Friar’s perspective underscores how AI can drive both efficiency and innovation in financial management, setting a benchmark for other industries to follow.
Offers a roadmap for integrating AI into finance operations, improving efficiency and risk management.
Provides actionable insights from a top executive on leveraging AI in traditional business functions.
- AI-native
- A business function or process designed from the ground up to leverage AI technologies for automation, analysis, and decision-making.
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