Project risk management has a problem that no framework has solved: the gap between what the standards say and what professionals actually do when uncertainty is real, data is imperfect, and decisions cannot wait.
This book closes that gap. It is written for project managers, risk analysts, cost estimators, and PMO leaders who work with uncertainty every day. Every chapter moves from concept to application, from theory to working model, from analytical output to stakeholder and boardroom-ready communication.
At its core, the book argues that probabilistic thinking is not a specialist skill. It is a professional discipline that every project practitioner can and must develop — and that AI, used correctly, makes that discipline more accessible, more rigorous, and more useful than ever before.
Drawing on over 25 years of consulting and training experience across energy, construction, utilities, and technology sectors, the author presents a framework in which best practice processes, Monte Carlo simulation, decision analysis, and AI language models are not separate tools but parts of a single integrated system for managing uncertainty in projects.
