AI-Ready Leadership

About the Course

AI has moved from the technology agenda to the leadership agenda, yet many leaders are expected to lead with it before anyone has equipped them to understand it. This flagship course closes that gap. It is not a tools or prompt-engineering course; it connects AI to what leaders actually own: strategy, decisions, operating models, and people. Participants build genuine AI fluency, assess data readiness, define human versus AI decision rights, and learn to govern an AI portfolio responsibly, closing with a working session to draft a concrete adoption roadmap for their own organization. Detailed work and team redesign is addressed in the advanced companion course, Leading Human-AI Teams and Redesigning Work.

What You Will Learn

• Explain AI and generative AI fundamentals, capabilities, and practical limits in clear business language, with no technical prerequisites
• Identify and prioritize AI opportunities by business value, feasibility, and risk
• Assess your organization's data readiness and strengthen the data foundations AI initiatives depend on
• Define human versus AI decision rights: what to automate, what to augment, and what must remain human
• Recognize the operating-model implications of AI adoption and evaluate build, buy, or hybrid choices
• Build trust and psychological safety during adoption, and lead experimentation without creating chaos
• Govern an AI portfolio with clear criteria for prioritizing, funding, scaling, and stopping initiatives
• Apply responsible AI practices spanning governance, ethics, risk, and the evolving regulatory landscape
• Design upskilling and reskilling paths that move whole teams, not only early adopters
• Build a concrete AI adoption roadmap for your own context, with sequenced initiatives, owners, and the measures that show whether adoption is producing business value

Key Topics & Agenda

• AI Fundamentals for Non-Technical Leaders
• Identifying Valuable AI Opportunities
• Data Readiness for AI
• Human Versus AI Decision Rights
• Operating-Model Implications and Build, Buy, or Hybrid Choices
• Trust and Psychological Safety During Adoption
• Leading Experimentation Without Creating Chaos
• AI Portfolio Governance
• Responsible AI, Governance, and Risk
• Upskilling and Reskilling Teams
• Measuring Adoption and Business Value
• Capstone: Building Your AI Adoption Roadmap

Related Roles

Executive / Senior Leader, People Manager / Team Lead, HR & People Professional, Product Owner / Product Manager, Change & Transformation Lead