How to run an AI pilot program in 30 days.
Turn experiments into evidence.

Most organizations are already running informal AI experiments. A structured pilot is different — you define what you're testing, how you'll measure it, and what you'll do with the results. In 30 days, you can go from 'we're trying some AI things' to 'here's what we learned and here's our recommendation.' Here's exactly how.

The difference between an AI experiment and an AI pilot is documentation.

Most organizations are already running informal AI experiments. Someone is using ChatGPT to draft emails. Someone else is using it to summarize reports. A few people are using tools leadership doesn't even know about. That's experimentation — and it's valuable. But it doesn't produce organizational evidence.

A structured pilot does. The difference isn't complexity. It's intentionality: you define what you're testing, how you'll measure success, what guardrails apply, and how you'll communicate what you learned. At the end of 30 days, you don't just have anecdotes. You have a results summary your leadership team can evaluate and act on.

Here's the exact framework for doing that.

Step 1 — Select the right workflow.

Not every workflow is a good pilot candidate. The best first pilots are:

• Specific and bounded — not "customer service," but "first-draft responses to tier-1 support tickets." The more specific, the more measurable.
• High-frequency — you need enough volume to produce real data in 30 days. Low-frequency tasks don't produce sufficient evidence.
• Low-stakes on errors — choose a workflow where AI errors get caught before they cause real problems. Save the high-stakes workflows for after you've built organizational confidence.
• Currently painful — the best pilots solve a real problem your team already has. If the workflow is already working fine, there's no motivating business case.
• Owned by one person or team — diffuse ownership makes pilots hard to run and harder to evaluate. One clear owner, one accountable team.

Step 2 — Write a one-page pilot brief.

Before anyone starts using AI on the workflow, write a brief that covers these six things. It doesn't need to be long — a single page is fine. What matters is that the answers exist and everyone involved has read them.

Step 3 — Run the pilot and document everything.

Run the pilot for 30 days with consistent documentation. You don't need an elaborate system — a shared spreadsheet or document works fine. What you need to capture:

• Time spent on the task before and after AI assistance
• Quality of AI outputs — where they were strong, where they needed significant revision
• Errors — what went wrong, how it was caught, whether the guardrails worked
• Team observations — what did the people doing the work notice?
• Unexpected use cases that emerged during the pilot

Good documentation turns a 30-day experiment into organizational evidence. It also builds the institutional knowledge that makes your second pilot faster and your third pilot even faster.

Step 4 — Write the results summary.

At the end of 30 days, produce a structured summary covering: what you tested, what you measured, what the results were, what you learned, and what you recommend as a next step. Keep it to one or two pages. This is the document you present to leadership — and it's the foundation for scaling what worked.

Related resources.

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