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

  1. 1Record the issue and location.
  2. 2Attach photos and instructions.
  3. 3Assign and chase responsibility.
  4. 4Check rectification and close the record.

AI-assisted workflow

  1. 1Classify and group incoming defect records.
  2. 2Extract stated location, trade and status.
  3. 3Prepare a close-out pack with evidence links.
  4. 4Flag incomplete records for review.

What a good workflow needs

Inputs, checks and useful outputs

InputsChecksOutputs
  • Defect report
  • Photos
  • Plans/location information
  • Correspondence
  • Inspection records
  • Photo/location attribution
  • Status and evidence
  • Safety or quality escalation
  • Inspection approval
  • Defect register
  • Trade action list
  • Close-out evidence pack
  • Draft follow-up

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