Gen AI for Complex Problem-Solving & Root Cause Analysis

Description
As systems grow more interconnected, leaders are increasingly confronted with ambiguous problems, hidden dependencies, and unclear failure patterns. Generative AI can accelerate how teams explore hypotheses, identify causal drivers, surface risks, and synthesize data, without replacing critical thinking. This workshop teaches participants how to combine classic problem-solving frameworks with AI prompting patterns to investigate issues more thoroughly, reduce bias, and develop clearer recommendations.

Course Objectives
Frame complex problems using structured prompting. Generate, compare, and evaluate hypotheses efficiently. Use AI to support root cause analysis (RCA) with proven frameworks. Identify hidden dependencies, constraints, and second-order effects. Synthesize qualitative data into themes and signals. Create more effective action plans and mitigation paths. Reduce cognitive bias using multi-lens prompting. Validate assumptions with scenario testing and counterfactual analysis.

Target Audience
Product, Project, and Program Managers. Engineering Managers and Tech Leads. Business Analysts and Operations Leads. Change Managers and Strategy roles.

Basic Understanding
Ideal for anyone tackling ambiguous issues with unclear root causes.