Chris Maloney

What is the background behind AI Metric?

More than twenty years in Tier 1 construction delivery. Not twenty years reading about construction, or selling software to it. Twenty years inside it, on real projects, with real deadlines, real risk and real consequences when the paperwork is wrong.

The depth is in complex facades and building envelope, commercial management, and dispute resolution. Those three are closer together than they look. Facade packages carry long lead times, heavy design interfaces and unforgiving tolerances, so they generate more change than almost any other package. Change generates commercial exposure. Commercial exposure, handled badly, becomes a dispute. Having worked all three ends of that chain is why the automation this company builds is aimed at the record, the notice and the time bar rather than at whatever demonstrates well in a meeting.

Why does that background change what gets built?

Because it changes what looks important. A consultant who has never defended a valuation will automate document formatting, because formatting is visible and easy to demo. Someone who has defended one will automate the contemporaneous record, because that is what decides the outcome eighteen months later when nobody can remember what happened on the day.

It also changes what gets refused. A method statement is not just a document, a common data environment is not just a folder, and a tool the site team resents will never be used no matter how good the business case looks. Knowing that from the inside means scoping the right problems and staying honest about where AI helps and where it must not be trusted.

What does he write about?

28 articles on this site, covering construction records, contract mechanics, private AI, and the practical business of getting sceptical construction teams to actually adopt a tool. Everything published here is written from delivery experience rather than from vendor material.