AI Evolution Checklist

1.

Run an AI 101 session/arrange some basic training

Give staff a plain-English introduction to AI: what it is, what it isn't, and how it can (safely) support their daily tasks. Our Introduction to AI workshops would be a great starting point.

2.

Define a company approach

Leadership to agree the overall approach: where AI should/shouldn't be used, target outcomes, and priorities,

3.

Draft a simple AI Acceptable Use Policy

Keep it short — outline what tools can/can't be used, data privacy rules, and when to double-check outputs.

4.

Nominate AI Champions

Identify 1–2 curious team members to test tools, gather feedback, and share learnings with others.

5.

Start small

Keep it short — outline what tools can/can't be used, data privacy rules, and when to double-check outputs.

6.

Choose safe, SME-friendly tools

Provide access to approved AI apps (e.g. Microsoft Copilot, Google Gemini, ChatGPT Pro) instead of staff experimenting with unvetted consumer tools.

7.

Encourage role-based exploration

Let each department try AI for their tasks (marketing, finance, HR, ops) and share success stories.

8.

Document early pilots

Write down what was tried, what worked, what didn't — so learnings aren't lost and mistakes aren't repeated.

9.

Track simple metrics

Start measuring time saved, emails written, or turnaround speed. Even light data helps prove value to the team.

10.

Feedback and celebrate successes

Hold monthly AI check-ins to gather feedback, surface risks, and share/celebrate wins (e.g. "AI saved us 2 hours this week!").