Dear colleagues,

I am writing from the Moselle Valley in Germany, at the end of a European tour that took us through FP&A Board meetings in Geneva, Zurich, and Munich. Thursday’s Munich meeting was especially energising, but one question kept surfacing in every discussion: when AI moves from analysis to action, who remains accountable?

That is where finance leaders are becoming more cautious. Asking AI to draft a comment, explain a variance, or summarise a forecast is one thing. Allowing it to trigger workflows, escalate exceptions, or shape decisions inside the finance process is another. The moment AI starts acting, governance cannot be added afterwards. It has to be designed into the work.

This issue shares a guide on agentic AI in finance, looking at how CFOs can capture value without losing control. We also bring together three articles from our FP&A thought leaders: why many organisations remain stuck in pilots, what governed AI decision-making looks like, and how control must be built before agents are allowed to act.

The webinars below take the same question into planning, data, and finance operating practice.

Warm regards,

Larysa Melnychuk, CEO and Founder
FP&A Trends Group & International FP&A Board

Agentic AI is moving from experiment to execution — and finance teams are in the spotlight. This new whitepaper, produced by FSN and Prophix, draws on the latest CFO research to show where AI agents deliver the most value and what responsible deployment looks like in practice.

Download your copy to discover:

• The AI dividend — where agents take on the heavy lifting across planning, consolidation, and reporting
• Responsible AI in practice — the governance frameworks and human-in-the-loop principles that separate trustworthy AI from risky AI
• The winning model — Why incrementally increasing autonomy as trust is earned works

Download Now 

AI pilots often look successful until finance asks a harder question: can this be trusted inside the monthly rhythm of decisions, reviews, and accountability?

Anjum Khan examines why adoption slows when data, ownership, change, and control have not caught up with the technology.

Read Anjum’s article on why AI pilots stall → 

The problem with AI-supported decisions is not that AI moves too fast. It is that governance often moves too late.

Tom Byrne shows how CFOs can structure evidence, policy gates, and accountability before AI recommendations begin shaping finance decisions.

Read Tom’s governance blueprint → 

Agentic AI can look useful before finance has decided who checks the work, challenges the output, and owns the consequence.

Leonard Schokker looks at why FP&A needs stronger control before AI agents move into planning and decision support.

Explore Leonard’s view on agentic AI in FP&A → 

FP&A Trends digital events are vendor-agnostic and complimentary. If you are not able to join the live session, you can register to receive the recording later.

AI is changing planning speed, but without strong business drivers, finance teams risk accelerating noise instead of improving decisions.

Register for this webinar to explore how driver-based planning strengthens forecasting, scenario visibility, and decision-making under volatility.

Most AI challenges in FP&A still begin with fragmented data, inconsistent definitions, and weak governance.

Join this webinar to learn how finance teams are improving data foundations to make AI more practical, scalable, and decision-ready.

AI is entering planning, forecasting, and decision support, but many finance teams are still unsure how to move from isolated use cases to practical augmentation.

Register for this webinar to examine what it takes to move AI from isolated use cases into daily finance work.