Articles on AI, project risk management, probabilistic thinking, and decision making under uncertainty.
The Strait of Hormuz is closed. Qatar has declared Force Majeure on 20% of global LNG. Forecasts are everywhere. Decision frameworks are not. This article builds one — combining a scenario probability tree, a BMMRJD time series model in @RISK, and Bayesian updating so you know exactly when to change your mind.
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Look at what is happening in the Persian Gulf and tell me you still believe in the single-point forecast. Three scenarios, three radically different futures — and organisations that do not model probability distributions are not managing risk, they are ignoring it.
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Teams adopt AI and move faster. Then something goes wrong — a risk flagged but never truly understood, a cost estimate that looked rigorous but wasn't. The research is now explicit: outsource the thinking, and you lose the capacity to think. Here is what correct AI use looks like in project risk management.
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Project management has no shortage of frameworks — yet outcomes remain inconsistent. The missing link is not methodology, but mindset. When probabilistic methods, simulation, and AI are integrated into everyday decision-making, the result is not certainty but resilience.
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As learning algorithms become embedded in cost forecasting and risk prioritisation, they subtly alter authority, accountability, and professional judgment. The key challenge is no longer technical accuracy — it is how to work responsibly with systems whose logic cannot be fully inspected.
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ChatGPT is not the last word in AI, just as Google was not the last word in search. The real asset is not which tool you choose — it is the skill to work with AI safely, fluently, and repeatedly inside real workflows.
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AI agents can now access files, reorganise folders, update spreadsheets, and execute multi-step tasks with minimal supervision. This is no longer speculation — it is operational reality, and exactly where structured risk thinking must step in.
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AI systems are crossing a threshold: from augmenting analysis to participating in coordination, interpretation, and decision authority. Drawing on Choudary's concept of "restacking," this article examines who holds agency when humans and AI work together on project decisions.
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