Aligned with Best Standards  ·  Live Instructor-Led  ·  No Specialist Software

PRACTICAL
PROJECT
RISK MANAGEMENT
WITH AI MODELS

Master the discipline of probabilistic thinking — powered by artificial intelligence. Two intensive days that change how your team thinks about uncertainty.

Request Programme Details See Programme
21
Contact
hours
8+
Practical
modules
3
Intensive
days
0
Coding or AI
experience needed
At a glance
📍
Format
On-site at your organisation or online. Live instructor-led throughout.
🗓️
Duration
3 days · 21 contact hours · 8+ modules
🌍
Languages
Delivered in English, Spanish, or French
📦
You take away
Excel Monte Carlo model · AI prompt library · Risk register template · Decision tree calculator
🎓
Alignment
PMI-RMP® framework · Taught by a PMI Authorised Instructor
THINK
Probabilistically
Move from single-point guesses to distributions, ranges, and confidence levels your decisions can actually rest on.
ANALYSE
Quantitatively
Build Monte Carlo simulations and decision trees in Excel — no specialist software, no coding required.
COMMUNICATE
Compellingly
Generate QRA and AI-powered dashboards and executive reporting that stakeholders understand and act on.
What your team gains

Capabilities that
stay after the training

This programme is built on a single conviction: the future of project risk management belongs to those who combine rigorous analytical discipline with the intelligence of AI. Participants leave not just knowing the theory — but applying it immediately on real projects.

  • ✓Implement a structured, repeatable risk management process aligned with project risk management best practices.
  • ✓Build high-quality risk registers using AI-assisted identification and classification.
  • ✓Run Monte Carlo simulations and sensitivity analyses in Excel — no specialist software needed.
  • ✓Use AI models to enhance both qualitative and quantitative risk assessments.
  • ✓Build and interpret decision trees, cost and schedule models, and scenario simulations.
  • ✓Produce compelling AI-generated risk narratives, dashboards, and executive briefings.
  • ✓Apply AI responsibly across documentation, stakeholder analysis, and response planning.
Who should attend

Built for
practitioners

📋
Project & Risk Managers
Running projects where cost, schedule, and uncertainty matter.
🏢
PMO Leaders & Analysts
Responsible for governance, reporting, and portfolio oversight.
📐
Planners & Estimators
Building cost and schedule models that need to reflect real uncertainty.
🤝
Consultants & Advisors
Supporting clients on complex infrastructure, energy, or technology projects.
📊
CFOs & Decision Makers
Anyone who needs to act on risk information — not just receive it.
Programme structure

9 modules.
2 days.
Real outputs.

Each module combines instructor-led teaching, live AI demonstrations, and hands-on exercises using your own Excel files. You work on real problems from the first hour.

00
Welcome, Framing & Learning Outcomes
  • The evolving landscape of project risk: uncertainty, speed, and complexity.
  • Why AI enhances — but never replaces — sound risk management practice.
  • Opening activity: surface your real risk management challenges.
01
Foundations of Project Risk Management
  • Standard project risk management framework: Plan – Identify – Analyse – Respond – Monitor.
  • What genuinely constitutes a risk vs. an assumption, constraint, or issue.
  • The case for structured, repeatable processes in complex project environments.
02
Building a High-Quality Risk Register
  • Powerful risk statements using Cause – Risk – Effect structure.
  • Risk Breakdown Structure, uncertainty types, probability/impact scoring.
  • Recognising cognitive biases — and how AI helps correct them.
  • Live demo: AI-assisted risk identification.
03
Quantitative Risk Analysis Essentials
  • Why probabilistic thinking outperforms single-point estimates.
  • Monte Carlo simulation: distributions, sampling, and interpreting outputs.
  • Cost, schedule, and integrated QRA fundamentals in Excel.
  • Sensitivity analysis, tornado charts, communicating ranges.
04
Practical Monte Carlo in Excel with AI
  • Selecting the right probability distribution for each risk variable.
  • Using AI to review model assumptions and flag logic errors.
  • Case study: build a working Monte Carlo model step by step.
  • AI-powered model validation and stakeholder expectation setting.
05
Decision Analysis with AI
  • Decision trees: structuring alternatives, probabilities, and outcomes.
  • Expected Monetary Value (EMV) for risk response selection.
  • AI-generated scenario narratives leadership can understand and act on.
  • Cost and schedule risk analysis for accurate project estimates.
06
AI-Powered Risk Reporting & Automation
  • Transforming raw risk data into executive dashboards and briefing packs.
  • Automating weekly updates, monitoring alerts, and lessons-learned capture.
  • Exercise: convert one risk register into three AI-generated communication formats.
07
Applied Case Study: End-to-End Risk Process
  • Full mini-project: identify, assess, quantify, respond, and present.
  • AI integrated at every step of the process.
  • Group presentations — each team delivers a polished risk output in 5 minutes.
08
Wrap-Up, Templates & Next Steps
  • Ethical and responsible integration of AI in professional practice.
  • Template pack: risk register, Excel Monte Carlo model, decision tree calculator, AI prompt library.
  • Personal action plan and instructor recommendations.
📄
Want the full programme details? The complete syllabus — including detailed module content, exercise descriptions, and delivery options — is available on request. Leave your details below and we will send it to you directly.
How it's delivered

Practical from
the first hour

🎯
Live Instructor-Led Demonstrations
Every concept is shown in practice — not just explained. Manuel demonstrates risk models, AI prompts, and Excel simulations live, adapting to the group's questions in real time.
📊
Guided Excel Exercises & Case Studies
Participants build real models during the session — not after. Monte Carlo simulations, decision trees, and sensitivity analyses are constructed step by step, with instructor guidance throughout.
🤖
AI-Powered Worked Examples
Every module integrates AI tools into the analytical process. Participants learn how to prompt, validate, and apply AI outputs responsibly — not just how to use the interface.
📦
Template Pack to Take Away
Every participant leaves with a working toolkit: an AI-enhanced risk register, Excel Monte Carlo model, decision tree calculator, and an AI prompt library tuned for project risk work.
In the room

Training that
has been tested
in the real world

Training session — Excel Monte Carlo model live
Live model build
Monte Carlo · Athens
Manuel Carmona presenting
Training audience — Athens
Small group training — Oslo
Corporate group
Oslo
UCL guest lecture
Guest lecture
UCL · London
Microsoft Athens · PMI Chapter event
Oslo · Corporate risk training
UCL London · MSc Infrastructure Finance
Prerequisites

No advanced
skills required

This programme is designed for practitioners, not mathematicians. If you can manage a project, you can take this course.

✅
Basic Project Management
Familiarity with project concepts. No formal certification needed.
📋
Basic Excel
Entering data and basic formulas. Advanced functions are taught during the programme.
🤖
No AI Experience
Required. All AI tools and techniques are introduced and explained from scratch.
💻
No Coding
Required. Everything is built in Excel or with AI tools — no programming whatsoever.
Request information

BRING THIS
PROGRAMME TO
YOUR TEAM

Available as an on-site programme for your organisation, or as an open-enrolment session. Delivered in English, Spanish, or French. Contact us and we will send the full syllabus and discuss your options.

🌍
Languages
English · Spanish · French
Request full syllabus
We will reply within one business day.