AI in finance is moving past experimentation and into execution, yet many organisations still struggle to turn promising ideas into tools that scale, integrate, and genuinely drive better decisions. This session breaks down what it takes to build effective finance AI products inside a complex enterprise, from defining the right problem to structuring the data foundations and earning adoption across the business. Drawing on real experience designing data strategy, analytics platforms, and machine learning use cases for global finance teams, this keynote explores how FP&A can partner with technology to create AI solutions that enhance forecasting precision, improve decision velocity, and strengthen enterprise performance. Attendees will walk away with a clear view of how to identify high-value opportunities, design models that align with business goals, and ensure the tools they build actually get used. Key takeaways: - How to identify the right use cases for finance AI and build business cases that resonate with leadership - How to structure data, modelling, and governance so AI products are reliable, scalable, and aligned to enterprise needs - How to drive adoption by designing tools that support real workflows and strengthen FP&A’s strategic influence