Everyone's Buying AI for Construction Data. Sam Rees Says You're Solving the Wrong Problem.

Walk the exhibition floor of any construction tech event and the pitch is always the same: bolt on an AI model and your project data starts working for you. Sam Rees, CEO of Hoppa, thinks that gets the order backwards. The model is the easy part. The reason AI keeps stalling on real projects isn't that the models aren't clever enough, it's that the data underneath them is a mess, and no amount of intelligence fixes a foundation that was never structured in the first place.

This week on the Project Flux podcast, Sam Rees joins James and Yoshi to talk about what it actually takes to turn raw project data into useful asset intelligence and why the construction and infrastructure industries keep tripping over the same first step.

🎧 Short on time? Hit play here — Sam on why structured data, not smarter models, decides whether AI works on your projects.

Rees starts with the uncomfortable truth about adoption. The industry isn't short of enthusiasm or short of tools; it's short of trust, and most of that scepticism is earned. Teams have watched "AI" land on top of disconnected spreadsheets, PDFs and handover documents and quietly fail, because the real problem which is unstructured, inconsistent, context-free data, was never touched. The core thing Hoppa sets out to solve isn't prediction or chat; it's structure: taking the sprawl of project information and shaping it into something a machine can reason over.

That's where domain expertise becomes the hidden ingredient. Rees is blunt that generic AI, pointed at construction data by people who don't understand construction, produces confident nonsense. His case study, an asset life-cycle analysis at an airport is the tell. The win wasn't that AI read the data faster, though it did, cutting work that took weeks down to a fraction of the time. The win was that the output meant something, because the people building the system knew what an asset register is supposed to say and what a surveyor or asset manager actually needs from it.

From there he zooms out to digital transformation generally, and why so much of it has quietly underdelivered. His read is that transformation stops being a slide deck and starts being real the moment the data layer is sorted and that the firms pulling ahead are the ones treating structured, trustworthy data as the strategy, not the AI tool they bought to sit on top of it. Get that right and the models become genuinely useful; skip it and you've automated the production of noise.

Why it matters: if you work in construction, infrastructure, surveying or PMO, the lesson is that AI's payoff is decided long before you choose a model. It's decided by whether your data is structured and whether the people doing the structuring understand your work. Spend on the foundation, not just the fireworks.

👉 Listen to the full conversation with Sam Rees here.

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