Date: June 11, 2026
FP&A professionals and controllers face increasing demands for faster forecasts and more responsive planning, yet many organizations still rely on slow cycles that delay decision-making.
This webinar examines how agentic AI reduces planning cycle times by continuously monitoring business drivers, updating forecasts as conditions change, and executing routine adjustments without manual intervention. We will compare AI agents to traditional automation, showing how agents can initiate chains of actions based on predefined thresholds rather than fixed schedules. Use cases include variance analysis triggers, rolling forecast updates, and scenario comparison.
Sponsors gain access to decision-makers evaluating modern planning platforms, position their solutions alongside BARC research on planning acceleration, and demonstrate capabilities to an audience already familiar with FP&A fundamentals and ready for practical implementation guidance.
