GenAI and Change Course

Lesson 1 • Ethical Baseline for GenAI Change

Introduces responsible AI principles as non-negotiable constraints on any change initiative. Ensures students embed ethics from the outset rather than as an afterthought.

Lesson 2 • Core Change Management Frameworks

Surveys leading change models and maps them to AI adoption contexts. Provides a conceptual toolkit students will apply throughout the course.

Lesson 3 • What Generative AI Actually Is

Defines generative AI, distinguishing it from traditional automation and predictive analytics. Grounds the chapter by clarifying what the technology can and cannot do.

Lesson 4 • Stakeholder Landscape in AI Projects

Identifies the roles affected by GenAI rollouts and their typical concerns. Sets the stage for stakeholder analysis techniques introduced later.

Lesson 1 • Readiness Dimensions and Indicators

Defines the key dimensions of organisational readiness: cultural, technical, and structural. Provides measurable indicators for each dimension.

Lesson 2 • Identifying Capability Gaps

Translates readiness data into prioritised capability gaps that block successful GenAI adoption. Introduces gap-mapping tools used in later planning chapters.

Lesson 3 • Building the Readiness Scorecard

Synthesises assessment findings into a visual, weighted scorecard for executive communication. Demonstrates how to translate scores into go/no-go recommendations.

Lesson 4 • Risk Profiling for AI Change

Identifies organisational, technical, and human risks specific to GenAI initiatives. Produces a risk register that feeds directly into the change plan.

Lesson 1 • Designing Engagement Strategies

Matches engagement tactics to stakeholder segments based on their readiness and influence. Covers co-design, early adopter programmes, and executive briefings.

Lesson 2 • Building Coalition and Sponsorship

Explains how to recruit and sustain an active sponsorship coalition that drives GenAI adoption. Links coalition strength to change velocity and sustainability.

Lesson 3 • Monitoring Stakeholder Sentiment

Introduces pulse surveys, sentiment tracking, and feedback loops to detect shifting stakeholder attitudes. Connects ongoing monitoring to adaptive engagement tactics.

Lesson 4 • Stakeholder Mapping Techniques

Applies power-interest grids and influence network analysis to GenAI project contexts. Produces a visual stakeholder map as the foundation for engagement planning.

Lesson 1 • Integrating Change and Project Plans

Aligns the change management plan with the technical project plan to prevent misaligned timelines. Demonstrates how to surface change tasks in project management tools.

Lesson 2 • Resource and Budget Planning

Identifies the human, financial, and technological resources required for each change phase. Teaches cost estimation techniques specific to AI change initiatives.

Lesson 3 • Phasing and Milestones

Structures the change initiative into logical phases with clear milestones and decision gates. Prevents scope creep and provides checkpoints for course correction.

Lesson 4 • Governance and Decision Rights

Establishes the governance structure that oversees the change plan and resolves escalations. Clarifies decision rights to prevent bottlenecks and accountability gaps.

Lesson 1 • Communication Planning Fundamentals

Establishes the objectives, audiences, channels, and cadence of a change communication plan. Provides a planning template students complete for their own initiative.

Lesson 2 • Two-Way Communication Channels

Designs feedback mechanisms that give employees a voice and surface concerns early. Connects two-way channels to stakeholder sentiment monitoring from Chapter Three.

Lesson 3 • Crafting AI-Specific Messages

Addresses the unique communication challenges of AI: demystifying outputs, addressing job fears, and explaining limitations. Teaches message framing that builds confidence without overpromising.

Lesson 4 • Leadership Communication Coaching

Prepares leaders to serve as credible, visible communicators during the AI change. Covers storytelling, Q and A preparation, and visible commitment behaviours.

Lesson 1 • Designing Blended Learning Programmes

Combines instructor-led, e-learning, and on-the-job practice into a coherent curriculum. Applies adult learning principles to maximise transfer to GenAI work contexts.

Lesson 2 • Building AI Literacy Across Levels

Differentiates training content for executives, managers, and frontline employees. Ensures every level understands GenAI relevance to their specific responsibilities.

Lesson 3 • Delivering and Scaling Training

Addresses logistics of rolling out training across large or distributed workforces. Covers train-the-trainer models, LMS deployment, and scheduling strategies.

Lesson 4 • Training Needs Analysis for GenAI

Identifies skill gaps between current workforce capabilities and GenAI-enabled role requirements. Produces a prioritised training needs matrix aligned to job families.

Lesson 1 • Monitoring Adoption Metrics

Defines leading and lagging adoption indicators and builds a real-time adoption dashboard. Connects metric trends to targeted interventions for lagging user groups.

Lesson 2 • Go-Live Planning and Execution

Covers cutover strategies, hypercare support models, and day-one readiness checklists. Ensures the transition from pilot to production is smooth and well-supported.

Lesson 3 • Managing Post-Launch Resistance

Addresses resistance that emerges after go-live, including workarounds and tool abandonment. Provides a structured intervention toolkit for change agents and managers.

Lesson 4 • Embedding Change in Culture

Transitions GenAI adoption from a project to a permanent organisational capability. Aligns HR systems, performance expectations, and leadership behaviours to sustain the change.

Lesson 1 • Assessing Human and Cultural Impact

Measures employee experience, engagement, and cultural shifts resulting from the GenAI change. Balances quantitative productivity data with qualitative human impact evidence.

Lesson 2 • Reporting Results to Stakeholders

Structures impact reports for executive, operational, and frontline audiences. Teaches data storytelling techniques that translate metrics into compelling narratives.

Lesson 3 • Measuring Productivity and Quality Gains

Quantifies efficiency, quality, and speed improvements attributable to GenAI adoption. Teaches attribution methods that isolate AI impact from other variables.

Lesson 4 • Defining Success Metrics Upfront

Establishes outcome metrics tied to the original business case before the initiative launches. Prevents post-hoc rationalisation and ensures accountability for results.