Using AI to validate and improve Traditional Agile project schedules to reduce risk of cost and timeline overruns – London
Abstract:
Every project manager has lived through it: a project schedule that looks complete—yet hides ambiguity, missing tasks, unrealistic durations, or poorly decomposed work. Whether in Microsoft Project, Jira, or Agile tools like Azure Boards, schedules often lack the level of detail needed to forecast risk, leading to cost overruns, missed deadlines, and stakeholder frustration.
This session demonstrates how AI can serve as a project schedule “risk validator”—a smart, objective reviewer that challenges assumptions, identifies missing decomposition, and strengthens schedule integrity before costly problems surface. Participants will see how to apply generative AI to test the quality of their project plans—regardless of methodology (Traditional/Waterfall, Agile, or hybrid).
Project teams often “planning to fail,” not because the work is impossible—but because the schedule conceals risk.
Through AI demonstrations, participants will see how to prompt an AI assistant to analyze any schedule and evaluate its: task granularity, labor work estimates, cost estimates, and staff resourcing.
The key takeaways for participants include:
- Quick review on the difference of such project management tools such as ADO and Microsoft Project to forecast vs management project work.
- How to use AI as a schedule risk auditor by detecting insufficient task decomposition, work estimates, and test your project forecasting assumptions.
- How to create an AI prompt toolkit where you can use ChatGPT, Copilot, or your preferred AI tool to improve schedule clarity and completeness.
PMI Talent Triangle: Ways of Working
