AI Opportunity Audit Template

Before you start

List every distinct area of the business you're auditing — departments, teams, or functions, whatever the real unit is here. Don't group anything together yet for convenience; a team that gets folded into "operations" at this stage usually gets skipped over later.

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The per-area worksheet

Copy this block once for each area on your list above. Filling in one properly is worth more than filling in all of them vaguely.

Area:

1. What does this area actually do, day to day? Not the job title. The real tasks, especially the ones nobody's written down because they didn't need to be.

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2. Where could AI plausibly help? Specific tasks, not "AI could help with admin." If you can't name a task, you haven't found a fit yet.

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3. What would it need to work well? This is the section most audits skip, and it's the one that decides whether the output is useful or generic. For each task above:

• Facts/spec it needs to be accurate:
• Tone or standard it needs to match:
• A real example of this done well already:
• What it needs to be told to leave out or avoid:

4. Is this actually a fit? Answer honestly, using the checks in the next section. If the answer is no, say so and move on — a clear "not yet, and here's why" is more useful to whoever reads this than a forced use case.

• Fit / Not yet / Indirect only (delete as appropriate)
• Why:

The honest no

Not every area belongs in an AI rollout, and pretending otherwise is how you end up with a tool nobody in that role actually opens. Use these checks before writing "fit" in section 4:

• Is the work mostly physical? If the task is manual, hands-on work, AI likely doesn't sit inside the role itself — it might still help one level up (forecasting, documentation), which is worth noting separately rather than forcing training onto people whose actual job doesn't change.
• Is the risk of an unreviewed mistake high and immediate? Anywhere output reaches a customer, a regulator, or real money with no review step, scope the use case narrowly (one specific task, checked) rather than opening the door broadly.
• Does the context this area would need actually exist anywhere? If nobody could hand over the facts, tone, and exceptions this area would need even if they tried, that's not an AI problem to solve yet — it's a documentation problem to solve first.

An area that fails all three isn't a training gap. It's an accurate finding, and it's worth stating plainly rather than working around it to make every department look included.

Once every area's done

Look across all the worksheets for the pattern, not just the individual entries:

• Which two or three areas have the clearest fit and the context to support it already available? Start there, not everywhere at once.
• Which areas came back "indirect only" or "not yet"? Note them honestly — revisiting in six months is a real plan; pretending they're covered isn't.
• Where the same missing context shows up in more than one area (a brand voice guide, a documented set of exceptions), that's usually worth fixing once, centrally, rather than solving per department.

This is the same worksheet behind an AI-adoption audit run across a real, multi-department retail business — see how it actually played out for the worked example. The gap between a generic AI rollout and a useful one is almost always what this document forces you to write down.