Enablement Lead
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Playbook · 9 min read

Your first 30 days as an AI enablement lead

A week-by-week plan to find what matters, get one team visibly better off, and report progress leadership believes.

In 60 seconds

  • Agree one sentence with your manager that defines what you're accountable for, so you're judged on outcomes rather than "adoption".
  • Replace the usage survey with eight 30-minute conversations, including two enthusiasts, two sceptics and two people who repeat the same task every week.
  • Score every task 1 to 3 on frequency, pain, fit and visibility, then commit to the top three and resist a fourth.
  • Run a one-week sprint with one team on their real work, and turn what you learn into a one-page workflow guide.
  • Report before-and-after numbers for the sprint workflow on a single page, not licence logins, and send it before the meeting.

By the end you'll have eight interview write-ups, three prioritised workflows with baselines, one team's before-and-after numbers, a one-page workflow guide and a one-page progress report.

You've been handed licences and told to "drive adoption". This playbook turns that into a concrete first month: eight conversations, three workflows, one team sprint, and a one-page report.

Most people who land in an AI enablement role inherit the same situation: licences have been bought, a few enthusiasts are flying, most people tried it once, and leadership wants to know when the productivity shows up. You've been told to "drive adoption". Nobody has said what that means.

This playbook is a plan for the first 30 days. It's deliberately small. The aim isn't to transform the company in a month. It's to end the month with three things: a true picture of how AI is being used today, one team visibly better off, and a way of reporting progress that leadership believes.

  1. Week 1: find out what people actually do.

    Eight 30-minute conversations across different teams and levels.

  2. Week 2: pick three workflows, not thirty.

    Score every task someone mentioned and set a baseline for the top three.

  3. Week 3: run your first enablement sprint with one team.

    A one-week sprint on their real work.

  4. Week 4: report progress in numbers leadership trusts.

    One page, sent before the meeting.

Before you start: decide what you're accountable for

Write one sentence and get your manager to agree to it. Something like:

TemplateYour accountability sentence
By the end of Q1, three teams will be using AI in a named, repeatable workflow, and we'll be able to show the time or quality difference.

That sentence protects you. Without it, you'll be judged on "adoption", which in practice means whoever is loudest in the leadership meeting. With it, you're judged on outcomes you chose and can influence.

Week 1: find out what people actually do

Instead, book eight 30-minute conversations across different teams and levels. Include two enthusiasts, two sceptics, and at least two people who do the same repetitive task many times a week. Ask:

ScriptDiscovery conversation questions
1. Walk me through the last time you used AI for work. What was the task?
2. What did you do with the output? Did you use it as-is, edit it, or throw it away?
3. What's a task you do every week that you'd happily never do again?
4. Have you been told anything about what you're allowed to put into these tools?
5. If this worked perfectly, what would you get back: time, quality, or something else?

Write up each conversation the same day, with the task, the tool, the outcome and the blocker. By Friday you'll see patterns. The blockers are usually one of four things: don't know what's allowed, don't know what it's good for, tried it and it was wrong, or no time to learn. Each needs a different fix, and you'll stop treating "adoption" as one problem.

Do this nowGet the discovery interview kit and script

Week 2: pick three workflows, not thirty

From your notes, list every task someone mentioned. Then score each one, 1 to 3, on:

  • Frequency: how often it happens, and across how many people
  • Pain: how much people dislike it, or how slow it is
  • Fit: whether current AI tools are genuinely good at it (drafting, summarising, restructuring, first-pass analysis) rather than things they're bad at (exact numbers, facts nobody's checked, anything needing live systems)
  • Visibility: whether a leader would notice if it got better

Pick the top three. Resist adding a fourth. A short list you can deliver beats a long list you can't, and it gives you a story: "We focused on the three highest-value workflows."

Do this nowScore and rank your candidate workflows

Week 3: run your first enablement sprint with one team

Choose the team with the best combination of a top-three workflow and a manager who wants this. Enthusiasm from the manager matters more than enthusiasm from the team.

Run a one-week sprint:

  • Monday (45 min): live session using their real work, not generic demos. Do the workflow together, start to finish, with the AI tool. Show the bad output as well as the good, and how you fix it.
  • Tuesday: give them a one-page guide for that workflow: the prompt or skill to use, what to check in the output, and what not to paste in.
  • Wednesday and Thursday: they do the workflow for real. You're on call in a chat channel. Every question is a sign of what the guide is missing.
  • Friday (30 min): retro. What did it take, compared with before? What went wrong? What would they tell a colleague?

Update the one-page guide with everything you learned. That guide is now a reusable asset, and the start of your library.

Week 4: report progress in numbers leadership trusts

Leadership doesn't want a usage dashboard. Licence logins measure activity, not value. Report three things:

  1. Before and after for the sprint workflow. "Monthly client reports went from about 3 hours to about 1 hour 15 minutes, across 6 people, roughly 10 hours a week back." Use the team's own estimates and say that's what they are. Honest rough numbers beat precise made-up ones.
  2. What you learned about blockers. "Most people aren't sure what data they can use. We need a one-page policy." This turns you from "the AI person" into someone who understands the organisation.
  3. What's next. The other two workflows, which teams, and what you need from leadership (usually: a clear data policy, time protected for training, and a sponsor in each team).

Mistakes to skip

  • Starting with training for everyone. A company-wide webinar feels like progress and changes almost nothing. Go deep with one team first.
  • Measuring logins. You'll get gamed numbers and lose credibility the moment someone asks what they mean.
  • Becoming the help desk. If every question comes to you, you can't scale. From week 3, write down answers so that the guide answers the next person.
  • Ignoring the sceptics. They usually have a real reason: it got something wrong, or they're worried about their job. Their objections are your best test cases.
  • Treating your own productivity as the result. You're probably already good at this. The job is the organisation's capability, not yours.

At the end of 30 days you should have

The next 60 days are about turning one team's win into a repeatable programme: champions in each team, a library of workflow guides, turning your best people's know-how into shared AI skills, and a measurement rhythm leadership will keep paying attention to. That's what the Role Book covers.

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