Module 2 of 6 · 25 minutes

Leading the change

People support what they understand and help shape. This module covers change frameworks and honest communication about AI.

Learning objectives

  • Build a case for change linked to what people care about
  • Apply ADKAR and Kotter to AI adoption
  • Communicate honestly about the impact on jobs
  • Plan two-way communication

2.1 Make the case for change

People change when they understand why. A good case for AI adoption connects to things your team already cares about — less tedious work, faster service, better decisions, staying competitive — and is specific about what will change and what won't.

2.2 Use a change framework

Established change models help you avoid skipping steps. Two widely used ones:

ADKAR (individual change)

Awareness of the need → Desire to take part → Knowledge of how → Ability to do it in practice → Reinforcement to sustain it. Diagnose which step a person is stuck on.

Kotter's 8 steps (organisational change)

Create urgency → build a guiding coalition → form a vision → enlist volunteers → remove barriers → generate short-term wins → sustain acceleration → anchor the change in culture.

For AI, the most common gap is between Knowledge and Ability: people attend training but never apply it to their real work.

Awarenesswhy change?DesireI want toKnowledgeI know howAbilityI can, in my workReinforcementit sticksthe usual AI gap: training not applied to real work
ADKAR: individual change moves through five stages. Diagnose where each person is stuck.

2.3 Talking honestly about jobs

Avoid both extremes — "nothing will change" and silence. Say what you know, what you don't, and what you're committing to:

An example message

"We're introducing AI to take on routine drafting and searching, so the team can spend more time with customers and on complex cases. Roles will change, and we'll redesign them with you, not to you. We're investing in training for everyone. We don't have every answer yet, and we'll share decisions as we make them."

Only make commitments you can keep. Trust lost through over-promising is very hard to rebuild.

2.4 Communicate often, in many channels

  • Leaders explain the why; managers translate it for each team
  • Share real stories from colleagues — what they tried, what worked, what didn't
  • Create two-way channels: Q&A sessions, anonymous questions, feedback forms
  • Repeat key messages — people need to hear things several times
  • Report progress, including what you've stopped or changed in response to feedback

2.5 Involve employee representatives

Where there are trade unions, works councils or employee forums, involve them early. In some countries consultation on new technology that affects work is a legal requirement. Early involvement usually produces better designs and smoother adoption.

Activity: draft your announcement

Write a short message (150–200 words) introducing an AI initiative to your team. Include: why, what will change, what won't, the support available, how to give feedback, and one honest unknown.

See a worked example

Checklist for your draft: Does it link to a goal the team cares about? Does it name specific tasks AI will help with? Does it say what support and training is offered, and when? Does it invite questions and say how? Does it acknowledge something not yet decided? Does it avoid promises you can't keep?

Key takeaways

  • Explain why, what changes and what doesn't.
  • ADKAR diagnoses individuals; Kotter guides organisations.
  • The common gap is from knowledge to ability.
  • Be honest about jobs; only promise what you can keep.
  • Communicate often, two-way, and involve representatives early.