Course Objective & Scope
AI does not make decisions, but used well it widens the option set, challenges assumptions and surfaces overlooked risks. The course applies decision trees, multi-criteria comparison matrices, scenario planning, pre-mortems and red-team perspectives with LLMs, while keeping accountability for verification with people.
Participants work on a real decision case from their unit and produce an assumption log, a scenario table and a reasoned decision memo. Verification checkpoints and the kinds of decisions where AI should not be used are also made explicit.
Who Should Attend?
- Middle and senior managers
- Strategy, planning and risk management teams
- Analysts preparing investment, procurement and product decisions
- Project sponsors and committee members
Key Takeaways
- Structure a decision problem with criteria, constraints and assumptions
- Generate alternative scenarios and counter-arguments with LLMs
- Expose hidden risks with pre-mortem and red-team prompts
- Recognise and reduce biases such as confirmation bias and anchoring
- Write a reasoned, traceable, human-approved decision memo
Curriculum
Structuring the Decision Problem
- Separating goals, criteria, constraints and assumptions
- Identifying information gaps with AI
Generating and Comparing Options
- Multi-criteria decision matrix and weighting
- Pros-cons and trade-off analysis
Scenario Planning and Sensitivity
- Optimistic, base and pessimistic scenarios
- Testing the sensitivity of critical assumptions
Pre-mortems, Red Teaming and Biases
- Failure scenario prompts
- Cognitive bias checklist
Decision Memo and Governance
- Reasoned decision memo template
- Human approval, traceability and the limits of AI
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