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Risk and Decision

Faster Models, Fewer Errors: An AI-Assisted @RISK Case Study

AI can dramatically speed up risk model-building—generating formulas, suggesting distributions, and compressing days of setup into hours. But it can also introduce subtle errors that are difficult to catch without the right verification layer. So how do you harness AI's speed without sacrificing rigor?

Join Manuel Carmona, PMI-RMP® Instructor, MBA, and Director at EdytrAIning, Ltd., for a live walkthrough of an energy-sector case study, where he'll demonstrate the full workflow of combining @RISK, the @RISK Agent, and AI tools into one integrated process.

On-demand

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Webinar speaker

Manuel Carmona

Risk and Decision Analysis Specialist, EdyTrAIning, Ltd.

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Manuel Carmona is an independent consultant, trainer, author, and PhD researcher at the University of Westminster in London, specialising in Artificial Intelligence, project risk management, and quantitative risk analysis (QRA). With more than 25 years of international experience, he has delivered hundreds of professional training programmes and coached thousands of practitioners in @RISK and Decision Tools Suite modelling, project risk management, probabilistic modelling, and Monte Carlo simulation. He is the author of Artificial Intelligence and Risk Analysis in Projects (Routledge) and Inteligencia Artificial y Análisis de Riesgos en Proyectos (Marcombo).

In this webinar, you'll learn how to:

Identify where AI accelerates model-building—and where it can mislead you

Use @RISK's tornado charts and scenario analysis to verify AI-generated assumptions

Integrate AI + @RISK to compress a two-day research and modeling cycle to 3.5 hours

Keep analyst judgment and validation at the center of every AI-assisted decision

Walk away with a repeatable process for building faster, more transparent, and fully defensible risk models—with confidence at every step.

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