AI evidence

Where AI is at work in the built environment.

Each dot is one of 301 published examples. Click a dot to read the case; the colour shows who reported it. Use the filters to find work like yours. Where the site of the work is not public, the dot marks the organisation instead.

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What do the sources report?

Hover or tap a dot to read the case. Use +/− or pinch to zoom, and Show all cases to reset. Dots that share a place are spread out slightly, so positions are approximate. Basemap © OpenStreetMap contributors.

Types of AI. Predictive AI spots, forecasts and optimises, for example image recognition, leak detection and scheduling. Generative AI writes and creates, for example chat assistants and drafting. “Both” means the same task uses both types; “Not stated” means the source does not say and the evidence is not enough to judge. “Judged from the evidence” means the source did not say which type was used, so 38thMove judged it from what the source describes.

Geography

Where the examples come from, as labelled.

Who reported it

Published studies and audits, the user’s own account, or a supplier or third party such as the press.

Sector mix

The built-environment sectors represented so far.

What's in the AI evidence library

The library tracks where artificial intelligence is being used and tested across the built environment. Every entry is based on a named public source. It includes live use, pilots, research tests, back-office use and a few useful examples from related sectors.

The map plots 301 examples across the Americas, Europe, Asia Pacific, Central Asia, Africa and the Middle East.

It is a curated collection of what has been published, not a survey of how widely AI is used. Being included is not proof of success, and a money figure is not necessarily an audited saving.

  • Construction and design: AI for project risk, rework, productivity, robotics and project controls.
  • Water & flood: network monitoring, leakage, wastewater and flood resilience.
  • Transport & rail: inspection, scheduling and infrastructure operations.
  • Energy, buildings & planning: asset management, smart buildings and planning automation.
How is AI being used in the built environment?

Across construction, water, transport, energy, real estate and planning, for project-risk and rework detection, asset inspection, network monitoring, scheduling, planning automation and more. Each entry is based on a named public account or study, not a general prediction.

What does each evidence case include?

The organisation or project, the asset, lifecycle stage, type of work and type of AI, who reported it, and whether its figures are reported results, estimates or targets. Where the source does not say which type of AI was used, 38thMove labels its own judgement.

How does the library support the advice?

It helps test whether a claim is isolated or recurring, who is making it, how strong the public evidence is and what a leader should ask before acting on it.

From evidence to decisions

Use the evidence to decide what to try.

The cases show what is possible. The innovation process and approach to working with AI agents help you find out what it is worth to you. 38thMove advises on priorities, fair tests and the changes needed to make them work.

  • Context: what experience says about the market, organisation and practical constraints.
  • Challenge: what the sources really support, where the claims are weak and what is still unknown.
  • Action: what to proceed with, test, narrow, pause or stop.
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Independent senior advice, based on experience and carefully checked public evidence.