AI will change how the built environment works. What will it be worth to you?
38thMove helps senior leaders in engineering, construction and infrastructure decide what to do about AI. The advice draws on 374 published AI examples, 53 surveys and more than thirty years in the sector.
AI is beginning to change how expertise is reused and how information leads to action. The examples below show specific changes in practice. Their effect on a whole business still needs testing.
Nomic describes Arcadis engineers turning technical reviews into reusable checks and verifying findings against project evidence. It reports one engineer’s structural reviews taking 67 hours instead of 185, without a published timing protocol or independent quality assessment.
Sharing useful checks can spread expertise. Measure the time and quality of accepted work before assuming a wider productivity gain.
Detailed supplier account undated. Arcadis separately announced its trial and investment on . Read the case →
900+ clearances
Sewer and pump operations
Yorkshire Water
StormHarvester describes AI alerts directing crews’ investigations. Its report says more than 900 blockages were cleared across the programme. The periods and overlapping counts are not fully reconciled; clearances are not a count of pollution incidents prevented.
The value comes when an alert leads a crew to find and fix a problem. Measure what changes after crews act.
Supplier report with named utility testimony. . Read the case →
Grid studies
AI prepares; engineers decide
Duke Energy
AWS describes Duke Energy using AI to prepare data and coordinate studies around established grid-simulation software. Engineers direct the study and make final decisions. The account does not establish a saving across complete studies.
Organise work around trusted engineering methods, and measure the complete study before assuming a capacity gain.
AWS launch account with a named Duke Energy quotation. . Read the case →
Each story shows its source date and limits. Older implementation experience also informs the wider assessment. See what the whole collection shows →
The evidence map
374 mapped examples from around the world. Click a dot.
Most conversations start with one of three questions.
There is no fixed package. Tell me what you would like to find out and we can work out together what would help.
“What does the evidence say about our work?”
An analysis of the database around your workflows, assets or market. It goes further than this site, with more detail and examples not published here. Where the evidence cannot answer your question, I will tell you so.
A second opinion before you invest: is the test fair, is the measure right, and what would it take to scale? Your team runs the work; you get an independent challenge.
I’m an engineer by background, with early career experience in academic research. During 32 years at Mott MacDonald, I worked as an engineer before becoming IT Director and later Global Chief Digital Officer. I also created Mott MacDonald Digital Venture, a new region focused on innovation, digital technology and new business models.
I founded 38thMove to bring that experience to leaders working through what AI means for their organisations. It connects practical engineering, leading change in a global business and developing new ways of doing business. 38thMove is deliberately small: you work directly with me, drawing on that experience and the evidence to explore your questions and decide what to do next.
I run 38thMove the way I suggest clients try AI: AI agents help me research, build the evidence collection and draft this site. The views and judgements are mine.
Why “38thMove”? In 2016, AlphaGo’s Move 37 looked wrong to expert observers, then proved brilliant and changed the game. 38thMove is about what happens next: how leaders respond once the game has changed.
Contact
What would you like to find out?
You don’t need a brief or a decision already in mind. A short note about what interests you or what you would like to understand is enough. I will reply personally.
