Dear colleagues,

A few months ago, I wrote that the tool does not define the outcome. The person behind it does. I would add something now: in Finance, the process behind the tool matters just as much.

AI is moving into workflows that were never designed for autonomous execution. Data still has to be reconciled. Exceptions need owners. Controls often depend on judgement that has never been formally built into the process. Our 2026 FP&A Trends Survey shows how much manual work remains: 47% of FP&A time is still spent collecting and validating data, while only 19% of organisations report advanced or best-in-class data quality.

This Digest issue looks at where automation should take over, where it should assist, and where Finance still needs to make the call. Here is a featured guide sets out six stages towards responsible AI delegation in financial consolidation. The selected articles take that question into practice, from deciding what is stable enough to automate to separating deterministic work from AI assistance and testing the forecasting logic underneath the model.

Good automation depends on knowing not only what the technology can do, but where Finance must remain in control.

Warm regards,

Larysa Melnychuk

CEO and Founder at FP&A Trends Group

Half of finance teams still take 6+ days to close the books. That’s not an AI problem. It’s a data, process, and control problem. Get those numbers wrong, and AI just helps you close faster with the wrong numbers.

The guide maps the six stages between where your close stands today and the work you can actually hand off to AI.

Inside, you’ll find:

• Where your close sits on the path to AI-readiness
• The three decisions that determine whether AI can be trusted with your numbers
• What you can delegate to AI, and why human judgement is still required
• A six-question self-audit to score your own readiness

Download now → 

The time saving from automation is easy to see. The harder question is whether the process deserves to be automated yet. Adam Szuly gives Finance a practical test built around repeatability, accessible data and removing dependencies on individual knowledge.

Read the automation filter → 

Not every close task should be handed to AI in the same way. Christian Martinez separates deterministic work such as calculations and mappings from GenAI-assisted commentary, with validation sitting between them. The useful lesson is the sequence: automate, validate, then explain.

Read the 30-day adoption sequence → 

A better algorithm cannot rescue weak steering logic. Andreas Seufert shows how AI makes fragile drivers, KPIs and decision routines more visible, turning forecast error into a signal about the management system underneath the model.

Read what weak forecasts reveal → 

Our webinars are free and educational, and help thousands of FP&A teams around the world learn together. Join live when you can, or register and we will send you the recording to watch in your own time.

The upcoming sessions move the discussion from individual workflows to the wider finance operating model: how teams adapt to AI, and how faster analysis is translated into better decisions.

FP&A transformation often stalls when adoption is treated as an afterthought. The discussion focuses on how leaders build trust, capability and behavioural change into new ways of working.

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Faster analysis does not automatically produce better decisions. The webinar examines how Finance builds decision intelligence by connecting planning, data and technology so teams can respond faster as conditions change.

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