Dear colleagues,

Most AI conversations in finance are still about possibility. The harder conversation — the one most leadership teams avoid — is about what is not working, what was oversold, and what it actually takes to make AI useful under real operating conditions.

In this issue, The CFO's AI Roadmap outlines a structured path forward, alongside articles that ask the less comfortable questions: what noise to stop consuming, where human expertise still has no substitute, and what groundwork one finance team had to build before any of it made sense.

I found these perspectives worth sitting with — and I think you will too.

Best regards,

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

There is no shortage of AI in finance right now. What's harder is knowing what's actually usable — under audit, across entities, within how your team already operates.

The CFO’s AI Roadmap gives finance leaders a practical framework to evaluate AI with clarity, without adding risk or complexity to an already strained function. Inside, you'll find out how to:

• Identify AI that holds up in real finance environments, not just in demos
• Avoid the hidden costs of tools that shift work onto your team instead of off it
• Apply a clear evaluation framework that works across entities, close cycles, and audit requirements

This is the resource finance leaders are using to move forward with confidence.

Download now 

By Ashok Manthena, Founder of ChatFin

There is a growing gap between how AI is discussed and how it is actually applied in finance. The louder the AI narrative gets, the harder it becomes to distinguish real capability from recycled hype. For finance leaders trying to make real decisions, the signal-to-noise ratio has never been worse.

Read this article to rethink your default response to AI information — and understand why filtering, not consuming, is becoming a core FP&A capability.

By Michael Coveney, Analytics Thought Leader and Author, Head of Research at FP&A Trends Group

The AI conversation often gets framed as a trade-off: automation versus human judgment. But in practice, the real challenge is not choosing between them — it is making them work together without slowing decisions down.

Read this article to explore how FP&A teams can integrate AI into decision-making without losing the one thing that still drives outcomes: human judgment.

By Stéphane Levratti, VP Group Financial Performance at IBA

Most AI strategies sound convincing until they hit the reality of systems, data, and internal resistance. What separates the teams that move forward from those that stall is rarely the tool. It is the foundation built before the tool goes in.

Watch this video to see what AI adoption actually looks like in practice — where sequencing, trade-offs, and groundwork matter more than the technology itself.

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.

June 10, 2026

When assumptions change, can your models instantly show the impact? The FP&A Trends Survey 2025 reveals that only 2% of organizations use dynamic, AI-powered driver-based planning—yet they achieve significantly higher forecast quality. Many teams still rely on static models and fragmented data, limiting their ability to respond, while AI enables real-time prediction and simulation; the real challenge is combining it with driver-based thinking to make planning more responsive and effective.

Join this webinar to explore how Driver-Based Planning in the age of AI is transforming forecasting and decision-making.

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