AI adoption strategy: let your teams build the change

Definition: An AI adoption strategy is the plan for how a business gets its people using AI safely and consistently in their work, covering the tools, the rules, the training and who owns what.

In short: The most effective AI adoption strategy we've seen is to let your teams build the change. Go wide first, with a hackathon that surfaces real problems and energy. Then go deep, with a design workshop on the best one, run by the people who'll use it and one person who makes the calls. The leader's job is to pick real problems, be in the room, and say yes quickly.

Change handed down from the top rarely lasts. People carry through what they helped build.

[Add a personal moment: what you saw change when a team built something itself.]

What is wide, then deep?

It's the approach we use, in two moves.

• Wide: many teams, one short event, lots of real problems. It surfaces the energy and the ideas, and shows leaders what people care about.
• Deep: one team, several days, the people who'll use the result and one decision-maker. It turns the best idea into something that works and that the team owns.

Wide finds the right problem. Deep builds the right answer.

What does wide look like?

At our UK summer party, six teams had one morning to build. The problems weren't invented. Our AI Champions picked six real ones from their own teams, and we mixed the teams so people worked with colleagues from outside their departments. By early afternoon, each team pitched a working prototype or solution design to the leadership team: five minutes to make the case, five for questions. Two ideas went live within a week, and it's now an annual fixture.

It worked because the people who'd use the ideas had built them, the leadership team had seen them work so there was nothing to persuade, and the problems were real from the start.

What does deep look like?

On one client project, a financial advice network wanted a better way to manage the work of one of its teams. We spent five days, seven hours a day, in a room with the people who'd live with the result: the team lead who'd own the solution, someone from security and architecture, the project manager, a business analyst, and a team member who explained what they actually do all day.

Instead of writing up what we'd heard, we built it and showed it. Each day we played back the solution as it stood. The team said what was right, what was wrong and what we'd missed. In the evening we reworked it, and came back the next morning with a better version.

Every question about how the solution should work went to the team lead. She'd tell us straight: I don't want that, or I do want this. She wanted one person to own each case from start to finish, so we dropped the random allocation we'd planned. Now that it's live, she makes changes to the platform herself and finds it easy. She started as a stakeholder and became a champion for change.

Your first 30 days as sponsor

A plan for a leader who wants to start. This is our proposed plan, so adjust it to how you'd really run it.

• Week 1: pick the problems. Ask your AI Champions, or team leads, to choose five or six real problems from their own teams. Name the person who'll make decisions on each.
• Week 2: run the wide event. Mix departments, give teams one morning to build, and hold the pitches yourself. Say yes or no on the day.
• Week 3: go deep on the best one. Put the people who'll use it in a room with one decision-maker, and play the solution back every day.
• Week 4: ship one thing, and measure. Take the best idea live, and ask your teams how it's going, so you can see what's changing.

The order matters more than the exact dates. Adjust it to your business.

Key takeaways

• Let your teams build the change. People carry through what they helped write.
• Go wide to find the right problem, then deep to build the right answer.
• As a sponsor, pick real problems, be in the room, give one person the authority to decide, and ship quickly.

FAQs

What is an AI adoption strategy?

An AI adoption strategy is the plan for how a business gets its people using AI safely and consistently, covering the tools, rules, training and ownership.

How do you get employees to use AI?

Involve them in building the change. Start with real problems from their teams, mix departments, let them build and pitch, and ship the best ideas quickly.

What is an AI hackathon?

A short, focused event where teams use AI to build a solution to a real problem, usually in hours rather than weeks.

What is a design workshop?

A working session where the people who'll use a new way of working help shape it, instead of reviewing a finished design at the end.

What is an AI champion?

An AI champion is a person in each team who runs training, shares what's working and feeds back what the team needs. We put one in every team across the UK and India.

How long should a hackathon or workshop be?

Our hackathon ran for one morning, with pitches in the early afternoon. Our design workshop ran five days. The important part is the loop: build, show, correct.

Who should take part?

For a hackathon, people from across the business, mixed by department. For a design workshop, the team lead who'll own the result, someone who knows the constraints, and someone who does the work every day.

Sources: Enate's own Team Readiness engagement, and a client project (anonymised). [Add link to the case study.]