Roundtable - The AI Reality Check: The Commercial Reckoning

Most leaders can now tell you what AI is doing inside their business. Fewer can tell you what it's actually returning.

Earlier this year, The Curve brought senior leaders together in Sheffield and Leeds for the first AI Reality Check. An honest conversation about what AI actually looks like inside real organisations, not the version in the vendor deck. Money came up last, but it was the theme the room agreed was moving fastest up the agenda.

Most leaders admitted they aren't yet measuring outcomes in any meaningful way, output was being tracked, not impact, and more than one described watching AI's cost quietly absorb the very efficiency it was supposed to create.

This session is the direct sequel. Same closed-door format, same commitment to reality over theory, one sharper question: is your AI actually paying for itself, or just staying busy?

For many businesses, the reality today looks something like this:

• Time saved by AI that never shows up as a number anyone can point to

• Licences and pilots quietly running without a clear owner of the return

• Efficiency gains that get absorbed into cost rather than turned into fee growth or capacity

• A live decision on whether to build tools in-house, buy them, or wait, with no clear framework for making that call

The opportunity is real. Proving it, consistently, is the part most organisations haven't cracked yet.

This is not a sales pitch for a measurement tool, and it isn't a lecture on ROI theory. It's a small, closed-door discussion for senior leaders and commercial decision-makers about what "AI pays for itself" actually means in practice, and how the organisations ahead of the curve are proving it.

Rather than focusing on hype or hypothetical value, the discussion will explore the commercial reality directly:

• Where AI is already delivering a number worth defending in a board meeting, and where it's just activity

• The efficiency tax: what happens when saved time isn't deliberately converted into value Build vs buy, and the genuine risk in commercialising something built quickly for internal use

• Whether pricing for outcomes, not hours, is a real option for your business or a distraction

• The timing question: what investing now costs, against what waiting costs instead

The goal of the session is simple: to move the conversation from "AI is doing things" to "AI is paying for itself, and here's how we know."

This will be a Chatham House ruled event. Places are limited to encourage open discussion. Breakfast will be provided.

Paul Ridgway

Paul is the founder and CEO With over a decade of experience leading technology businesses at both CEO and CTO level, Paul knows what it takes to scale teams, systems and services. He’s managed teams of 80+ developers and worked closely with leaders across operations, product and engineering, from the boardroom to the build room.

Paul brings a rare combination of technical fluency and commercial clarity, with ability to truly align technology with business growth. He’s driven by a mission to replace overengineered, underperforming solutions with purposeful technology that works.

Simon Devine

Simon co-founded Hopton Analytics, building it into a Microsoft Solutions Partner for Data and AI serving mid-market businesses across the UK and Ireland. He leads the commercial side of the business and stays close to client work, because he thinks that's where the interesting problems are. Before Hopton, Simon was Operations Director at a leading Microsoft Dynamics partner.

That grounding in Microsoft business applications shapes how Hopton approaches analytics and AI: not technology for its own sake, but tools that change how a business actually operates day to day. Simon is a regular speaker on data and AI, and is based in Yorkshire, where Hopton is proudly headquartered in Leeds.