Project Controls
Delay Analysis in the Age of AI: A New Approach to Time Impact Analysis
Key Takeaways
- TIA requires contemporaneous records — AI tools can help capture and structure these records in real time
- Automated schedule fragnet generation reduces TIA preparation time by 40-60%
- Expert engineering witness remains essential — AI supports, not replaces, the analytical process
The TIA Challenge on Complex Programmes
Time Impact Analysis is fundamentally a forensic exercise: it requires reconstruction of the as-planned programme, identification of delaying events, and quantification of their net impact on the critical path. On a mega-project with hundreds of concurrent activities, thousands of RFIs, and a programme history spanning several years, manual TIA preparation is extraordinarily resource-intensive — often running to six-figure professional fees for a single delay event.
Where AI Accelerates the Process
The most time-consuming elements of TIA preparation — document review, schedule event mapping, fragnet construction, and contemporaneous record compilation — are all candidates for AI-assisted automation. Tools that can ingest programme updates, RFI logs, instruction records, and daily reports, then automatically map them to schedule activities and identify critical path impacts, can reduce TIA preparation time by 40-60% without compromising analytical rigour.
The Importance of Contemporaneous Records
The best TIA preparation tool is the one that helps capture the right records at the time of the event — not six months later when a claim is being compiled. TCE's project controls deployments include a contemporaneous record protocol as standard: every delay event is logged, evidenced, and mapped to the programme at the time it occurs. When a TIA is subsequently required, the analytical framework is already in place — dramatically reducing the cost and time of expert analysis.