AI literacy for leaders, and the teams behind them.

1. SESSION 01 · 90 MIN

   Building your mental model

   Separate hype from reality. Understand the AI stack and where AI fits.

2. SESSION 02 · 90 MIN

   Realising value from AI

   Find the high-value opportunities. Understand the economics. Plan how capability evolves.

3. SESSION 03 · 90 MIN

   Budget, governance and roadmap

   Evaluate vendors. Build the business case. Take ownership of the rollout.

• Understand what AI can and cannot do

  Recognise realistic uses of AI and avoid common misconceptions.

• Identify where the value is

  Spot where AI saves time, reduces effort or sharpens decisions.

• Link AI to business outcomes

  Connect AI ideas to measurable impact rather than hype.

• Make better technology choices

  Ask the right questions when evaluating tools and vendors.

• Govern AI with confidence

  Put the right controls in place without slowing the business down.

• Lead AI adoption as a team

  Direct the discussions, decisions and roadmap — no deep technical expertise required.

An Executive Playbook, an AI Opportunity Canvas, a Budget Template, a Vendor Scorecard and a Roadmap Template — plus a reading list drawn from OpenAI, Google, Anthropic, Microsoft and Harvard Business Review.

1. PART 01 · ~20 MIN

   What's real, what's hype

   Cut through the noise: an honest read on what today's AI does, and doesn't, do.

2. PART 02 · ~35 MIN

   How AI actually works

   The plain-English mental model — and the shared vocabulary to talk about it without the jargon.

3. PART 03 · ~35 MIN

   Where it fits your work

   Mapped to your team's real work and shown live — worked examples of where AI helps, where it doesn't, and what stays human.

4. PART 04 · ~20 MIN

   Starting well, and safely

   Simple first steps, the guardrails that matter, and how to keep the momentum after today.

• A shared, honest baseline

  Everyone leaves with the same realistic read on what these tools do and don't do.

• One vocabulary across the team

  Fewer conversations talking past each other — one language for AI.

• A sense of where it fits

  Each person sees where AI helps their own day-to-day work.

• Confidence, not hype or fear

  The team can try the tools knowing what's worth the effort.

• A safe way to start

  Simple guardrails so people can experiment without creating problems.

• Momentum to build on

  People leave wanting to try things — and with a sensible first step to take.

A shared AI vocabulary, a simple map of where AI fits your team's work, and a starter set of safe, high-value first uses — plus a short reading list to keep the momentum going.

1. PART 01 · GROUND

   Start on the same page

   Open with the AI fundamentals — shared language and a clear mental model — then straight into your work.

2. PART 02 · BUILD

   Set the tools up for real value

   Hands-on: repeatable workflows, recurring tasks, skills and agents — built on the tools you already use.

3. PART 03 · COMPOUND

   The competency to keep going

   The patterns and understanding so the team sets up its own next workflows, without us.

4. PART 04 · SCOPE

   Spot what goes beyond copilot

   Capture the opportunities that need bigger builds or integrations — so you know where a copilot stops and a system starts.

• Something working you can keep

  A workflow, skill or agent built in the room that the team keeps using and improving.

• The competency to do it again

  Your people understand how the tools work and how to set them up — so they build the next ones themselves.

• More from the tools you already have

  Real productivity from ChatGPT, Claude, Copilot and Gemini — the tools you already pay for.

• Set up properly, not generically

  Tuned to your tools, your team's level and your real use cases.

• Where copilots stop, a system starts

  A practical view of what needs a bigger build — and the opportunities worth taking further.

• Judgement kept where it matters

  A clear view of where to keep a human in the loop.

Your copilots set up properly on your own tools, a working workflow, skill or agent to keep refining, the patterns to build the next ones, and a shortlist of opportunities that go beyond copilot.