Most finance teams are already experimenting with AI. Far fewer are seeing consistent, defendable financial return. The gap is rarely about tools. It’s about where AI is applied, how processes are redesigned around it, and how outputs are trusted enough to influence real decisions. This session moves past concept slides and into how finance leaders are embedding AI into forecasting, close, working capital optimisation, and decision support in ways that stand up to audit, board scrutiny, and real operational pressure. Expect a clear look at where AI is already reducing cycle times, improving forecast accuracy, and unlocking capacity across finance teams, alongside honest lessons from implementations that didn’t deliver as expected. You’ll leave with a practical view of what is working today, where ROI is showing up fastest, and how to prioritise use cases that create measurable enterprise value rather than incremental efficiency. Key takeaways: Where CFOs are seeing the fastest, most defensible AI-driven financial returns across FP&A, close, and cash management How leading teams are redesigning workflows so AI removes work instead of adding review layers What “board-ready” AI outputs look like and how finance teams are building trust in models and insights