Spotlight Retail 2026

Move from explaining last month to actively steering next week.

Turn two reactive outcomes into the proactive tools they should be.

Three concrete AI roles already doing the work, built for retail finance

Present:

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13:00 - 14:00

Online

Retail CFOs don't doubt their team's capability. They doubt the system their team works inside. By the time finance has a clear picture, the business has already moved on and no amount of extra effort closes that gap.

The problem isn't your team. It's the setup.

Margins shift before the dashboard refreshes. Inventory decisions made last week are already affecting cash positions today. Finance is still explaining what happened instead of steering what's next.

The effort is high. The impact feels low. That gap isn't a people problem — it's an architecture problem.

Working harder inside a system that's structurally one step behind the business doesn't close the gap. It just makes the gap more exhausting. Something needs to change. Not the people. The setup.

What you'll leave with

An hour of substance, built around two things you can actually use:

A working framework for the Buy vs. Build AI decision. Demoed in front of you, not described in a slide. You'll see what a finance professional built themselves, and leave with a way to judge your own next move.
A next step you can act on the following week. Not a whitepaper, a concrete way to test where your own setup stands.

What we'll cover

Session 1: Buy or Build? AI-powered cashflow forecasting in retail

Your cashflow forecast is already out of date by the time it reaches you. Most retail finance teams are still building weekly cash views manually. Reconciling bank feeds, chasing actuals across entities, running scenarios in spreadsheets. Meanwhile, the cost of doing this differently has dropped fast. What used to take a development team 18 months now takes one person a weekend.

In this session, we make that shift concrete. We open by showing a working AI cashflow forecasting tool, built by a finance professional, not a technology team, over a weekend. Real-time scenario modelling, automated anomaly detection, natural-language cash queries.

Then the decision you're actually facing:

‍Buy a solution: faster, lower risk, vendor accountability and SLAs — at the cost of data control and differentiation.‍
Build your own: full ownership, proprietary capability — but you own the errors, the maintenance, and the delivery risk.

Both sides get an honest hearing. You leave with a decision framework and the one question to ask yourself before committing either way.

What this session answers:

What does AI cashflow forecasting actually look like when a finance professional builds it themselves?
How much does a stale cash forecast really cost and what would real-time visibility have changed?
If you buy a tool like Palm, what are you trading away and is that trade-off worth it?
If you build your own, what does it actually take and when does it make sense?
When does Build start to beat Buy? Has that tipping point already arrived?

Built for finance leaders in retail

This event is for CFOs, Finance Directors, Heads of FP&A, and Directors Business Control accountable for margin, cash, and forecasting accuracy — in finance, business control, financial systems, or treasury.

If you've ever felt like effort is high and impact feels low, this session was built for you.