September 17, 2026
0 minutes to read

CMap x Building Webinar Recap | AI and the bottom line

Tom Purves

Senior Marketing Content & Partnerships Executive

Tom Purves is Senior Marketing Content & Partnerships Executive, creating engaging B2B and SaaS content for the AEC industry that drives engagement, and leads key partnership efforts.

Every firm is under pressure to do more with less, and AI keeps getting pitched as the answer. But what does that actually look like day to day, and does it show up anywhere in your margin?

That's the question CMap set out to answer with Building, bringing together four voices from across engineering, architecture and professional services technology: Derek Murray of Mott MacDonald, Adam Bushnell of AtkinsRéalis, David Rockhill of Arcadis, and CMap's own Tom Rains. Four presentations, one live Q&A,and a fair amount of hard data on where AI is actually moving the needle on profitability today.

Here's the recap.

Derek Murray: Digital strategy lead at Mott MacDonald

A lot of the software this industry runs on was designed decades ago, and the biggest time sink for engineers, architects and project managers has always been finding information rather than using it. At Mott MacDonald, AI-assisted technical assurance is now checking and coordinating thousands of drawings and documents across a notoriously fragmented supply chain, cutting processing time by "tens of percent" in some cases. Margin doesn't only move one way, either: sometimes AI's job is protecting it, or helping a firm absorb more scope without asking for more fee. The real barriers are shifting AI clauses in client contracts, the pace of change, and making sure the next generation of engineers still learns from the current one.

Adam Bushnell | Regional digital lead at AtkinsRéalis

AI needs to be a value story, not just an efficiency one. AtkinsRéalis frames commercial value around three levers: reducing effort on repeatable, lower-risk work; freeing up scarce specialist time for what actually matters; and using AI to augment expert judgement rather than replace it. In the water sector, that's meant AI evaluating far more network investment options, far faster, with engineers still making the final call. Chasing efficiency alone caps the upside; the bigger prize is better decisions and better outcomes.

David Rockhill | Global service executive at Arcadis

The standout stat of the session came from Arcadis's work with New York City's Environmental Protection department, where permits that used to take 60–90 days were slowing down hundreds of millions of dollars of flood-prevention work. Rather than bolting AI onto the existing process, Arcadis redesigned the workflow from scratch and built AI in, lifting throughput by 40–50% and cutting errors. Elsewhere, a partnership with AI platform Nomic across 200+ projects has already saved over 2,000 engineering hours. Arcadis groups the value into four buckets: faster project delivery, freed-up capacity, sharper commercial decisions, and entirely new client offerings that weren't feasible a few years ago. The common thread: start with the business problem, not the technology, and make sure your commercial model lets you actually capture the value you create.

Tom Rains | Product marketing manager at CMap

CMap's own survey of our customers puts a number on the gap everyone's feeling: 80% have started adopting AI, but only around 1 in 5 can point to a measurable return. Most of that activity is personal efficiency - drafting an email, a first-pass concept - rather than anything structural. CMap Intelligence, launched earlier this year, is built to close that gap: Fee Estimation Intelligence surfaces a client or sector's past project performance the moment a new quote is being built, and Resourcing Intelligence recommends project teams based on real skills and availability rather than the same familiar faces. The firms actually seeing AI move their margin are the ones treating it as a deliberate, strategic layer, not a collection of individual habits.

From the Q&A

A few themes ran through the discussion regardless of who was answering. Start with the most tedious, repetitive workflow, not the flashiest use case. Build the data foundation around one workflow at a time rather than trying to fix everything at once. Treat AI's environmental impact as a genuine business-case line, not something to bolt on afterwards. And bring people with you: the firms making real progress are the ones explaining the "why" and making the value of their data visible, not just automating quietly in the background.

Wrapping up

Thanks to Derek, Adam, David and Tom for a genuinely useful hour, and to everyone who joined live or has caught up since. If you're eager for more, you can watch the full webinar, or you can catch up on plenty of our other webinars here.

If you want to go deeper on how CMap helps AEC firms turn this into a repeatable, margin-positive process, our team would love to talk.