Week one: try it yourself. Pick a task you do regularly — a newsletter draft, a social media post, a meeting summary — and try doing it with AI. Compare the result to what you’d normally produce. Note what’s useful and what’s not.
Month one: pick two or three use cases. Based on your experiments, identify the tasks where AI saves the most time for the least risk. Common starting points: social media drafts, grant application structuring, and meeting note summaries.
Month two: draft your policy. Now that you know how your team is likely to use these tools, write a simple AI use policy. Share it. Discuss it. Make it a living document.
Quarter one: review and expand. What worked? What didn’t? Where are the bottlenecks? Adjust your approach and consider whether paid tools would deliver better results than free ones.
A note on timing. If you tried AI tools a year or two ago and weren’t impressed, try again. The improvement between early 2024 and early 2026 has been dramatic — particularly in understanding context, following complex instructions, and producing usable first drafts. And if you’re worried about investing time now when the technology might be quite different in six to twelve months — that’s understandable, but once you’ve built basic AI literacy in your team, adapting to new or improved tools is straightforward. The skills transfer. Getting started is the hard part; upgrading is easy.
