How to choose an AI consultant for a construction business.
Seven practical tests for choosing an AI consultant who understands construction workflows, data risk, adoption and commercial payback.
Most construction and built-environment companies know AI is coming but not where it actually pays back. That's our work: a transformation partner that finds where AI saves you real money, what to fix first, and what to trust, before a single system is built.
AI isn't the risk. Standing still is.
Before you roll AI out across your company, you need to know whether it will save money, improve margins, and give your senior team time back.
Every engagement transforms three things: the tools you work with, the way the work flows, and the people who run it. We do it through the same four stages. We diagnose what's actually leaking time and margin. We build the AI that fixes it. We train your team to live with it confidently. We stay close enough to make sure the systems keep working months after launch.
We start with how the business actually runs. Where the senior leadership team are losing days every month to work a system should be doing. Where revenue is walking out the door because enquiries go unanswered. Where compliance risk is one step away from costing you real money. We come back with a written diagnostic of where AI saves you money, and just as importantly, where it doesn't.
How we diagnoseWhat we uncover
We build the systems that fix the leaks we found in the diagnostic. Each one is shaped around the value at stake: senior hours returned, margin protected on every job, revenue captured before enquiries go cold, compliance handled without burning the team's time. The systems work alongside the tools your team already uses, not against them. And we sequence the work so the first system is fully in place before the second one starts.
What we buildWhat we deliver
A system that no one in your business can confidently use is a system that doesn't pay back. We train your team inside the systems themselves, on live work and real outcomes. By the end, everyone in the business uses the AI confidently, knows how to improve it, and can spot where it should take on more. That's how AI keeps earning its place long after launch.
How we train your teamWhat we cover
A system that lands well and is still used six months later is the one that gets embedded with the team. We stay close after launch, watching how the system actually sits inside the day-to-day, refining what's not quite right, and adding what's missing. As the business grows, the systems grow with it: new workflows added when they're worth adding, existing ones tightened up, quarterly reviews keeping the build plan honest. We act as the AI side of your business.
How we stay embeddedWhat we maintain
An illustrative blend of recovered time, avoided mistakes and won contracts
Run the AI opportunity assessmentWasted on rework
28%
Of project time on the average build is lost to rework. Add the 18% spent hunting for information that should be to hand, and close to half of every project's hours never move the job forward.
Procore, Future State of Construction
On the table
15%
The productivity lift available from digitising how a construction business runs, alongside 4–6% off the cost base. On a £10M operation that's £400,000–£600,000 back, every year.
McKinsey, Reinventing Construction
Almost no one
<1%
Fewer than one construction company in a hundred has AI properly embedded across operations. The ones who move first set the pace.
RICS, AI in Construction
Those are the industry numbers. Here's ours: a built-environment company in live delivery right now, the diagnostic delivered and the build in progress. We'll publish the results the moment they're ours to share.
The shape of the work
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We send regular notes from inside the work: what is moving in AI for UK construction and the built environment, the workflows worth fixing, and worked examples you can act on. Read them as they land and you compound a real edge over the firms still waiting to see what happens.