Meet Uncut: Extra Filling - May 2025

That was the real theme behind the latest GENCFO Meet in London. Sure, the agenda said “AI in finance,” but the actual conversation turned out to be way more grounded—and frankly, more useful. Chris Argent hosted the session and was joined by three sharp, straight-talking experts: Rajiv Chandra from Virgin Media O2, Maria Olympha Preston from Luca Faloni, and Matt Glock from Keboola.

They didn’t talk about the latest AI tools or dashboards. They talked about the stuff most of us are quietly dealing with—disconnected data, unclear ownership, teams still stuck in spreadsheets, and the huge gap between the promise of tech and the reality of day-to-day finance.

Can AI Fix Bad Data?

Let’s be honest: not yet. Rajiv put it bluntly—“You can’t automate chaos.” And he’s right. Most finance teams are trying to layer AI on top of messy, outdated systems and hoping it’ll magically work. But unless the data is structured, owned, and trusted, it just won’t.

This hit home with a lot of people in the room. We’re all under pressure to move fast, but the basics still aren’t in place. AI is only as smart as the data we feed it. And if that data is junk? Well, so are the insights.

Are We Mistaking Tools for Transformation?

Maria raised a point that’s probably true for more teams than we’d like to admit: we expect tech to do the transformation for us. But you can’t plug in a new system and call it strategy. She talked about needing to rework team structures, roles, and communication—because most so-called “tech issues” are actually people issues.

If your team isn’t working well together, isn’t clear on who owns what, or doesn’t feel confident with digital tools, no AI is going to fix that. You’ve got to start there first.

What’s the Point of Tech If People Don’t Understand It?

Matt made the case that what we really need is more digital confidence—not more dashboards. If your team doesn’t know how to ask the right questions, how will AI help them answer anything?

This isn’t about turning everyone into data scientists. It’s about making sure your people can work with data, interpret it, and feel empowered to use it in their decisions. Otherwise, even the smartest tools just become another layer of complexity.

Are We Equipping Our Teams or Just Expecting Them to Keep Up?

Audience questions were spot on. One person asked how to deal with execs who still think Excel is “fine.” Another shared that their team was struggling to keep up with new platforms because they hadn’t had the training or support. These aren’t fringe cases—they’re common.

The panel agreed: leadership needs to stop assuming and start supporting. Give people the time, tools, and training they need to actually work in a more digital way. Otherwise, we’re just piling pressure on without building capability.

Have We Earned the Right to Automate?

That was maybe the most powerful question of the night. Everyone wants to automate, but have we really put in the work to make that automation meaningful? If the data is unreliable, if the team doesn’t trust the output, if decisions are still made by gut—then what exactly are we automating?

Rajiv summed it up: “AI isn’t a strategy—it’s a multiplier.” It can make good systems great, but it won’t rescue bad ones.

So, Where Should You Start?

The panel didn’t offer a silver bullet—and honestly, that’s what made it valuable. Instead of selling solutions, they asked better questions. And those questions stuck with people long after the session ended:

Are your people confident using data?

Do they know who owns what—and are they equipped to improve it?

Are you investing in culture and capability before pushing more tech?

Because that’s the real takeaway: if your team isn’t ready, no platform is going to bridge the gap. Want AI to work? Start with your people.