AI is already reshaping finance operations — but not in the way most headlines suggest. For finance leaders, the real challenge isn’t whether to adopt AI, but how to embed it into core workflows while maintaining control, accountability, and trust.
This Reuters Events webinar cuts through the noise to examine how autonomous finance is being applied today — inside real finance functions, supporting real decisions, and operating within established governance frameworks. No futurism. No unchecked automation. Just practical progress.
Designed for CFOs, finance transformation leaders, and controllership teams, this report focuses on what works, what doesn’t, and where autonomy genuinely adds value right now.
Speakers include:
Prithwijt Chaki, Global Finance Advisory Leader, Genpact
Sri Ghattamaneni, Field Engineering Leader, Databricks
Michael Nicosia, VP ADUSA Finance Data, Reporting & Analytics, Ahold Delhaize USA
Moderator – Eva Chalioti, Senior Lecturer, Yale University, Economics of AI
Enterprise AI leaders will discuss:
- Automation vs. autonomy — and the data gap in between — why most enterprises stall at automation because their data foundations aren’t ready; the shift from siloed financial data to a governed, unified data layer as the prerequisite for AI agents that act, not just assist.
- Data-led transformation in action — Deep dive into 2–3 core finance workflows (AP, R2R, FP&A) where modern data platforms and agentic AI converge, enabled by centralized finance data foundations (e.g., governed lakehouse architectures)
- Trust, governance & human-in-the-loop — How unified data governance (lineage, quality, cataloging) underpins trust in autonomous systems, with accountability frameworks for AI-driven financial decisioning.
- CFO playbook: From pilots to scaled production — Practical guidance on sequencing the journey — data modernization → agentic capabilities → production scale — with 3/6/12-month milestones and the role of strategic tech partnerships.
Why this matters now
As finance functions face growing pressure to do more with less, autonomy is moving from experimentation to execution. But progress depends on credibility, not vision. This report provides a realistic blueprint for embedding AI into finance operations — safely, responsibly, and at scale.
