Adopt: leading AI adoption
Building support and momentum in your team
The leader becomes the credible champion of AI in their team. The leader becomes the credible champion: narrative, visible role modelling, psychological safety, support conversations and team norms. This module deliberately does not repeat tool training; it develops the leadership behaviours that convert tool availability into embedded team practice.
Six to eight weeks
Four live sessions and three applied sprints
Cohorts of 10 to 14
Level-specific cohorts for relevant peer learning
Priced by proposal
Starts with a scoping conversation
Why this module exists
AI adoption is a leadership practice, not a software rollout
Technology can make AI available. It cannot make a team trust the direction, understand what is changing, or know where responsible use begins and ends. That work sits with the leader. The Augmented Leader Suite is built around that reality: leaders learn in live facilitated experiences, then apply the work to their own teams between sessions.
The leader becomes the credible champion: narrative, visible role modelling, psychological safety, support conversations and team norms. This module deliberately does not repeat tool training; it develops the leadership behaviours that convert tool availability into embedded team practice.
This module is self-contained, so an organisation can commission it on its own. It also forms one part of the wider suite: Adopt builds support and momentum, Operate redesigns work around human-AI collaboration, and Transform stewards workforce transition, culture and responsible AI. Each module contributes a finished part to the Team AI Playbook, a living operating guide owned by the client.
The approach is intentionally practical. Participants bring a real team, workflow or area of accountability. They leave sessions with a deliverable to test, a peer conversation to hold and a decision about what to observe. This is not a promise of a generic uplift or a substitute for technical implementation. It is a structured way to make leadership behaviour visible while AI-enabled work changes.
Programme facts
What this module includes
| Who it is for | Team leaders and people managers leading AI adoption; level-specific cohorts of 10 to 14. |
|---|---|
| Format and length | Four live sessions and three applied sprints over six to eight weeks; virtual-first with a face-to-face option, peer triads and no video or e-learning content. |
| Output | Four live sessions, three applied sprints, six to eight weeks. Virtual-first, with a face-to-face option. Builds Part One of the Team AI Playbook. Leaders apply the work to their own real team or area of accountability; each part of the Team AI Playbook is client-owned. |
| Investment | A module cohort is priced by proposal after scoping. Separate single workshops in the Leading with AI library collection start from £850; this is not a cohort price. |
This module is not an accredited qualification or a promise of certification. If a formal credential is the priority, compare CMI's Leadership for AI qualifications at Levels 3, 5 and 7 with providers directly; this programme is designed for applied leadership behaviour and client-owned workplace outputs.
Why now: make AI adoption visible and safe
Deloitte's UK GenAI workforce survey (published 16 September 2026) found that 63% of its respondents knowingly used GenAI for work. Of GenAI users, 31% said they used it without their employer's knowledge and 65% reported a lack of convincing organisational leadership on how it should be used; around half of users had received no formal training in safe and effective workplace use. Among weekly GenAI users, 64% worried managers would think GenAI could do their jobs. These are not percentages of all UK workers: Ipsos UK surveyed 25,000 employed and self-employed UK workers aged 18–70 online using representative quotas between 7 May and 10 June 2026; the GenAI-user base was 16,749.
CMI's Artificial Intelligence; Real Leadership research (10 June 2026) polled more than 1,000 UK managers: 13% strongly agreed senior leaders actively used AI tools, and 12% said they were “very confident” managing teams using AI. These are responses to separate questions, not measured effects of training.
Shadow AI is the use of generative AI tools for work without the employer's knowledge or approval. A leader's response is not just to provide access: it is to give the team a clear purpose, practical guardrails, visible role modelling and room to discuss mistakes. To see where your own team stands, the Shadow AI Exposure Check is a 15-statement team reflection on guidance, training, tool access, stigma and disclosure norms. The AI Team Charter helps make those expectations explicit.
The module starts with an AI Adoption Leadership Diagnostic baseline and uses an adoption pulse with a later sponsor review to track practice, not just attendance. For a second individual starting point, explore the AI Confidence Assessment. The reference card supports the manager behaviours between sessions; read more on moving from AI anxiety to AI confidence.
What participants practise
Objectives and outcomes
By the end, leaders can
- Construct and deliver a credible team narrative about AI adoption that addresses role uncertainty honestly and survives sceptical challenge.
- Model visible, regular AI use in leadership work, sharing successes and failures deliberately.
- Apply psychological safety practices to design and run team AI experiment cycles with explicit permission to fail.
- Diagnose each team member's adoption readiness and hold tailored one-to-one support conversations.
- Co-create team norms for responsible AI use covering data, quality assurance, disclosure and escalation.
- Build and operate a 90-day reinforcement plan covering recognition, measurement and barrier escalation.
Evidence of application
- A team narrative delivered and refined in response to team reaction.
- The leader's AI use visible weekly, with at least one failure shared openly.
- Two or more team experiment cycles, each with a whole-team debrief.
- Support conversations held with every team member, prioritising those previously avoided.
- Team AI norms co-created, agreed and in visible use.
- A 90-day reinforcement plan live, with systemic barriers logged and escalated to the sponsor.
The learning journey
Four sessions, three sprints, one real context
Four live sessions, three applied sprints, six to eight weeks. Virtual-first, with a face-to-face option. Builds Part One of the Team AI Playbook. Each session is spaced so that leaders can test an idea at work, return with evidence and use peer learning to improve the next move. Distributed practice is a deliberate design choice: Cepeda et al. (2006) found that spacing learning over time supports retention better than compressed practice.
Week 0 · milestone
Launch communications, readiness check and pre-programme reflection
Week 1 · session
Session 1: The Leader's Adoption Mandate
Weeks 1–2 · sprint
Sprint 1: Personal AI working week plus draft team narrative
Week 3 · session
Session 2: Making Experimentation Safe
Weeks 3–4 · sprint
Sprint 2: Run the first team experiment cycle
Week 5 · session
Session 3: Support Conversations and Team Norms
Weeks 5–6 · sprint
Sprint 3: Adoption conversations plus team norms agreement
Weeks 7–8 · session
Session 4: Embedding and Sustaining Adoption
Tools leaders keep using
The module is designed to leave performance support behind, not just a memory of a workshop. Its practical tools are:
Delivery touchpoints
- Sponsor-signed launch message
- Four live sessions (or two face-to-face days plus one virtual embedding session)
- Three applied sprints with real-team deliverables
- Peer triads meeting between sessions for 45 minutes
- Facilitator office-hours drop-in
- Week 8–12 transfer check with pulse measure and sponsor review
Start with a baseline
Diagnostic, resources and adjacent thinking
AI Adoption Leadership Diagnostic
Assess adoption mandate, role modelling, experimentation, support conversations and sustaining adoption.
Take the diagnosticLeading AI Adoption Reference Card
A concise reference for the behaviours, questions and practices in this module.
View the resourceLeading AI Adoption Development Planner
Turn diagnostic results into priority actions, a 90-day focus and accountability.
View the plannerMeasurement and evidence
Measure transfer, not just attendance
The programme starts with a diagnostic baseline and returns to observable workplace evidence. The exact measures are agreed with the commissioning organisation because the useful signal depends on the module: adoption pulse and sponsor review for Adopt; workflow metrics and team wellbeing pulse for Operate; transition metrics, governance gaps and culture signals for Transform.
That makes the outcomes above a set of evidence to work towards, not a guaranteed claim about every organisation. Growth Performance can help leaders agree what to observe before delivery, how to gather a baseline and when to review transfer. The accompanying planners support monthly practice; peer triads create a structured place to test assumptions and notice barriers.
The programme sits alongside the wider leadership development ROI approach, the 4Cs Framework and The Augmented Us. It does not claim that a diagnostic alone proves business impact, or that a training intervention can replace product, legal or workforce expertise.
Research and framework notes
The suite record draws on published evidence and frameworks including distributed practice, identity leadership, human-AI complementarity and responsible AI governance. Explore the sources and original Growth Performance material: Cepeda et al. (2006), Distributed practice in verbal recall tasks · The Augmented Us: identity leadership for AI-augmented teams · The Augmented Leader: three shifts for leaders · The 4Cs Framework.
Questions buyers ask
Frequently asked questions
Who is Leading AI Adoption for?+
It is for team leaders and people managers who need to turn AI availability into responsible, supported team practice. Participants bring a real team context rather than learning generic tool features.
How long does the AI adoption leadership programme take?+
The module runs over six to eight weeks: four live sessions, three applied sprints and continuing peer support. A transfer check takes place in weeks 8 to 12.
Is this an AI tools training course?+
No. The module develops the leadership behaviours that make adoption stick: credible narrative, visible role modelling, safe experimentation, support conversations, team norms and reinforcement. It does not repeat tool training.
Can Leading AI Adoption be delivered virtually?+
Yes. It is virtual-first and can also be delivered with a face-to-face option. The learning remains live and applied rather than video-based or elearning.
What diagnostic and resources support the programme?+
The AI Adoption Leadership Diagnostic provides a five-dimension starting point. Participants can then use the Leading AI Adoption Reference Card and Development Planner, alongside the programme's adoption tools.
How much does the programme cost?+
The module is priced by proposal, beginning with a scoping conversation. We do not publish a generic suite price because scope and context are agreed with the commissioning organisation.
Ready to discuss Leading AI Adoption?
Start with the context you have: the leadership population, the AI change under way and what you need people to do differently. We can use a scoping conversation to establish whether this module, the full suite or another intervention is the right fit.
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