In this article, Ashok Manthena reflects on what 2025 really delivered for AI in FP&A — cutting through hype to explain where value emerged, where transformation stalled, and what must change to turn noise into signal.

Join this FP&A Trends webinar to learn how leading organizations connect planning across strategy, finance, and operations to improve forecast quality and decision-making, based on global survey insights and a discussion with experienced FP&A leaders.

Join the face-to-face Seattle FP&A Board on March 19th to explore a roadmap to success through FP&A Predictive Planning and Forecasting.

In this article, the authors explain how diversity of thought, lived experience, and empathy can strengthen FP&A teams’ ability to navigate uncertainty and support better decision-making.

Check out the recording of the FP&A Trends Webinar, to get a grounded view from senior finance practitioners and thought leaders on how FP&A roles are evolving, which skills will matter most, and what leaders can start doing now to build a more resilient, future-ready team.

In this article, we summarise key insights from the latest FP&A Trends webinar on how finance teams can prepare for the era of Agentic AI, covering data and culture readiness, practical use cases, and role evolution for FP&A professionals.

At the 29th AI FP&A Committee Meeting, Adam Hancock, VP FP&A at EBSCO Industries, shared how AI is already part of day-to-day FP&A work across 14 portfolio companies.

In this article, forecasting frequency is examined through the lens of data maturity, leadership behaviour, and decision impact—challenging the assumption that more frequent forecasts automatically create more value.

In this article, you will learn the most common pitfalls in driver-based forecasting and the practical steps FP&A leaders can take to build scalable, transparent, and scenario-ready models.

This digest brings together reflections on why forecasting remains fragile, where confusion with planning weakens outcomes, and how some teams are improving forecasting instead of trying to perfect it.