AI for Change Management

This course contains the use of artificial intelligence for entrepreneurs. AI tools are used in the production of this course, including AI-assisted speech delivery based on the instructor's own voice. All content, demonstrations, workbooks, and prompts have been personally designed, reviewed, and verified by the instructor to ensure accuracy and practical value.

Change management is being rewritten. Generative AI and automation have compressed change cycles from quarters into weeks, put AI-generated analysis into everyday decisions, and pushed automation into knowledge work itself. The frameworks most of us trained on — Kotter, Prosci and their peers — were designed for slower, more linear change, and several of their assumptions no longer hold. This course is a practical, hands-on guide to leading change in an AI-native organisation. You will not just learn about AI — you will use it, on real change work, in every section.

No technical background is needed, and no coding is involved. You will build a working mental model of the four AI layers that matter — generative AI, predictive and analytical AI, agents and tool use, and enterprise integration — then apply them across the tools your organisation actually uses: ChatGPT, Claude and Microsoft 365 Copilot in Word, Excel, Teams and PowerPoint. You will master a five-part prompt structure that turns AI into a reliable drafting partner for leadership briefings, stakeholder emails, FAQs, change plans, risk logs and training content, and build a reusable prompt library for your team. You will work with agent mode and automated workflows, learning where to place human checkpoints and how to supervise delegated work. Each of these sections closes with a practical exercise and a role play, so you leave with both a finished artefact and the rehearsed experience of the conversation that goes with it.

From there, the course walks the full change lifecycle: AI-supported discovery and readiness assessment, change strategy and design, communications, engagement and training, then adoption, reinforcement and measurement. You will look at functional and sector use cases, role-based adoption pathways, and the human side that decides whether change sticks — fear, fatigue, deskilling, trust, transparency and clear human accountability. Again, every section ends with a hands-on exercise and a role play — briefing a sceptical stakeholder, handling a difficult adoption conversation, defending a plan under pushback — so you are practising the human side of change, not just reading about it.

Finally, you will build the governance to do this responsibly: risk management for agentic workflows, a workable AI governance operating model, and an AI adoption roadmap and capability plan for your own team. As with every section, you finish with a practical exercise you can run on a live initiative and a role play you can rehearse before you take it into the room. By the end you will have a repeatable AI-enabled change method, a prompt and template library, and the confidence to lead AI adoption — rather than be led by it. Enrol now and start applying it to your next change programme this week.