Navigating the GenAI Transformation

Navigating the GenAI Transformation

Empower leaders and managers to co-create an AI-enabled organization guided by purpose, trust, and strategic vision.

One day

In an era where Generative AI isn’t just a tool but a workforce game‑changer, leaders must transcend mere adoption to craft a future where AI augments human ingenuity. This intensive one‑day course equips executives and managers with transformative strategies—spanning strategic vision, human‑centered design, governance, and culture change—to not just implement AI, but to embed it meaningfully into business operations.

Anchored in deep industry insight and real‑world applicability, this course delivers actionable frameworks to inspire confidence, drive adoption, and ensure Generative AI becomes a business enabler—not a liability.

Learning Outcomes

Participants completing this course will be able to:

1. Articulate a clear, purpose‑driven AI “North Star” that aligns with organizational vision and business outcomes.
2. Design and lead a strategic roadmap for GenAI adoption with measurable goals and quick‑win demonstrations.
3. Establish trust through governance and oversight, combining data accessibility and responsible AI practices.
4. Redesign workflows and operating models to integrate AI as a capability—not just a tool.
5. Drive change with people-first transformation, enabling experimentation, upskilling, and employee engagement.
6. Support leaders through the transition with frameworks for communication, championing, and iterative adaptation.

Prerequisites

• A basic understanding of AI / GenAI—what it does and its business potential.
• Representation from leadership, middle management, and change agents for integrated perspective.
• Access to organizational strategy documentation, current workflows, and data governance policies.
• Commitment to pilot learning, open culture, and willingness to iterate.

Detailed Course Outline

1. Framing the Transformation
   • 1.1 Why GenAI? Purpose beyond hype
     • The imperative: Why ask “why?” before adopting AI.
     • Learn from real-world missteps (e.g. Commonwealth Bank’s AI misfire) and the importance of human-centric, phased adoption.
   • 1.2 Defining the “North Star” for GenAI
     • Outcome-focused vision over tool deployment.
     • Map your organization across potential tiers: manual, AI-augmented, agentic swarms.

1. Strategic Roadmapping for Leaders and Managers
   • 2.1 Building a GenAI Strategy Roadmap
     • Identify high-value, ROI‑driving use cases; move from pilots to scaled workflows.
     • Adopt strategic pillars: Vision, Values, Risks, Adoption.
   • 2.2 Leadership Roles & Governance
     • Role of CAIO or equivalent in integrating AI strategy, risk, and oversight.
     • Responsible AI governance: ethics, policy, oversight frameworks .
     • Build an AI oversight committee, human-in-the-loop checkpoints to manage hallucination and bias risk.

1. Reimagining Workflows & Operating Models
   • 3.1 Embedding GenAI as Capability
     • Redesign from discrete AI tool use to integrated agentic workflows .
     • Balance: high-touch customer areas vs back-office automation, and progression to minimum viable organizations (MVOs).
   • 3.2 Workflow Evolution Phases
     • Phase 1: AI aiding specific tasks
     • Phase 2: Swarms of AI agents managed by humans
     • Phase 3: Agentic swarms delivering outcomes with human oversight .

1. Building Trust: Data, Governance & Transparency
   • 4.1 Establishing Trust Infrastructure
     • Accessible data ecosystems + quality governance = trust.
     • Morgan Stanley case: rigorous evaluation led to 98 % adoption among wealth managers.
   • 4.2 Ethical, Transparent AI Use
     • Adopt responsible AI frameworks and transparency standards.

1. People‑Centered Change & Culture
   • 5.1 Leading with First Principles: Reframe AI as Human Enabler
     • Emphasize human creativity and empathy aided by AI.
   • 5.2 Change Management Pillars
     • Forbes‑Council: Leadership, Data readiness, Workforce empowerment, Roadmap with quick wins.
     • Nerdery: Vision, transparent communication, culture of experimentation, agile feedback loops, recognition .
     • Prosci: People-first approach leveraging ADKAR for AI transformation
   • 5.3 Skills & Engagement Tactics
     • Training, Lilli Clubs (McKinsey example): employee‑led agent creation
     • Singtel’s AI Academy training 10,000+ employees.

1. Iterate, Measure & Scale
   • 6.1 Agile Pilot Learning
     • Rapid experiment-feedback loops, celebrate early wins.
   • 6.2 Metrics, ROI & Long‑Game Strategy
     • Track ROI, adoption, productivity improvements.
   • 6.3 Sustaining Change Muscle
     • Embed continuous transformation capability.