Practical AI training built around your team’s work.

Most AI training teaches tools, and the tools change every few months. I teach teams to test whether AI helps with their own work, a skill that outlasts any tool. Every session and pack is built on tasks your team recognises, with time to practise and to check the results.

Discuss training for your team

Tell me about the team, what they do and what you want them to do differently.

Your team has AI tools. Mostly, it uses them for quick drafts.

A few people use AI well. Most ask it for a first draft, tidy it up and stop there. Nobody has shown them how to give it the context a real task needs, how to check what comes back, or what is safe to put into it in the first place.

That gap is what the training closes.

Choose the format

Hands-on workshops

In person, for one team. People bring real tasks, test AI on them and leave with a first experiment and an owner for it.

Virtual training

The same hands-on approach, delivered online, for teams that work remotely or across sites.

Training packs

Exercises, worked examples and output checks built around your team’s tasks, for people to work through and keep using.

Start with the work you want to improve

The useful starting point is a task your team recognises: preparing a report, reviewing a piece of work or turning information into a usable first draft.

We agree the audience, their current experience and the intended outcome before I shape the session. The tools and examples follow from that, whether your team uses Copilot, ChatGPT, Gemini or something else.

What your team will practise

01
Choosing a task that is worth testing with AI.
02
Briefing AI well: the context and instructions the task needs.
03
Checking accuracy, completeness and suitability before anyone uses the output.
04
Using AI safely and within your organisation’s policy: what can go into a tool, what cannot, and where a person checks before anything goes out.
05
Comparing the result with the current way of working.
06
Deciding what to keep, change or stop.

The steps follow The Edge Loop, the same method behind my consultancy and implementation work, taught on your team’s own tasks.

Turn the training into a next step

The aim is for people to leave with an approach they can repeat and a clear test to run on their own work. We agree what participants should be able to do before the session, so the training has a practical finish line.

When a task turns out to be worth building properly, that becomes an AI implementation conversation, scoped separately.

Explore AI implementation

Agree the details before committing

We agree the audience, learning outcomes, format, preparation, materials, follow-up and fee before booking. If the need also involves building a workflow, we define that separately.