Generative AI Strategic Leader Specialization course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

Overview (80-120 words) describing structure and time commitment.

Module 1: Foundations of Generative AI for Leaders

Estimated time: 10 hours

  • Introduction to generative AI concepts from a leadership perspective
  • Understanding Large Language Models (LLMs) and their capabilities
  • Limitations and misconceptions of generative AI
  • Real-world business applications of generative AI

Module 2: Generative AI Strategy and Business Transformation

Estimated time: 14 hours

  • How generative AI reshapes competitive advantage
  • AI-driven innovation, efficiency, and growth opportunities
  • Strategic frameworks for prioritizing AI initiatives
  • Aligning AI with business model evolution

Module 3: Governance, Ethics, and Risk Management

Estimated time: 8 hours

  • AI ethics, bias, and transparency in enterprise contexts
  • Regulatory and compliance considerations for AI
  • Mitigating risks like hallucinations and data leakage

Module 4: Leading AI Adoption and Change Management

Estimated time: 12 hours

  • Leading cross-functional AI implementation teams
  • Managing organizational change due to AI integration
  • Building AI literacy across leadership and workforce
  • Strategies for workforce transformation and upskilling

Module 5: Capstone: Generative AI Strategic Roadmap

Estimated time: 16 hours

  • Designing a generative AI strategy for a real or simulated organization
  • Defining vision, priorities, and governance structures
  • Establishing success metrics and long-term value creation plans

Prerequisites

  • Familiarity with basic business strategy concepts
  • Experience in leadership or managerial role preferred
  • No technical background required

What You'll Be Able to Do After

  • Explain generative AI and LLMs in non-technical, strategic terms
  • Identify high-impact AI use cases across business functions
  • Evaluate AI opportunities, risks, and ROI at the organizational level
  • Develop governance models for responsible AI adoption
  • Create an actionable, business-aligned AI strategic roadmap
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