Project control
AI for Construction Defects, Evidence and Close-Out
AI can turn defect reports, photos, location notes and correspondence into a structured register and close-out pack. It cannot inspect workmanship, decide compliance or accept rectification on behalf of the person responsible.
Last reviewed: 23 September 2026 · General information only. Contractual, statutory, professional and safety decisions remain with the appropriate authorised people.
The construction problem
Where the work gets stuck
Defect lists become unreliable when photos, locations, responsibility and status are recorded differently across teams.
Current manual workflow
- 1Record the issue and location.
- 2Attach photos and instructions.
- 3Assign and chase responsibility.
- 4Check rectification and close the record.
AI-assisted workflow
- 1Classify and group incoming defect records.
- 2Extract stated location, trade and status.
- 3Prepare a close-out pack with evidence links.
- 4Flag incomplete records for review.
What a good workflow needs
Inputs, checks and useful outputs
| Inputs | Checks | Outputs |
|---|---|---|
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Human control
The responsible inspector or authorised person determines defect status, acceptance and close-out.
Example
How this looks on a real job
Three photos show a repeated finish issue but two lack location. The system groups them and flags missing context; the superintendent decides whether they are one defect or several.
Related resources
Sources and further reading