Most organisations don't have an AI problem. They have a people problem and a process problem. This checklist helps you see both clearly. Work through each section honestly. The more questions you can't answer confidently, the more valuable a structured AI Adoption Gap Audit will be for your business.
How to use this checklist
Click each box you can answer confidently. Leave blank if you're unsure or the answer is no. Count your ticks using the score guide at the bottom.
I can name the top 3 tasks that eat the most admin time in my team each week.
If you can't name them, you can't fix them.
I know roughly how many hours per week my team spends on repetitive, manual tasks.
Repetitive = same steps, same format, same output, every time.
I have documented at least one end-to-end process in my team (even informally).
AI can only automate what you can describe clearly.
I know which of our processes involve copying information from one system to another.
This is almost always an automation opportunity.
Our operational data — customers, orders, staff, finances — is stored digitally, not primarily on paper or in physical files.
Paper-first systems need to be digitised before automation is possible.
Our data is reasonably consistent — fields are filled in the same way by different people.
Inconsistent data (different date formats, name spellings, etc.) breaks automations.
We have a single source of truth for key business data, not multiple spreadsheets that may conflict.
Multiple sources of truth is one of the most common blockers to AI adoption.
We know where our data quality gaps are, even if we haven't fixed them yet.
Knowing the problem is the first step. Ignoring it means AI will just make errors faster.
My team generally responds well to new tools and process changes.
Resistance isn't a reason to avoid AI — but it needs to be planned for, not ignored.
My leadership team is aligned on exploring AI in the business.
Without leadership buy-in, even the best automation will stall.
I have at least one person in my team who is curious about AI and willing to champion it.
You need an internal champion. It doesn't have to be you.
My team understands that AI is meant to reduce admin, not reduce headcount.
This fear is almost universal and needs to be addressed directly and early.
I have a basic understanding of what AI tools like ChatGPT or Copilot can and can't do.
You don't need to be technical — but you do need a working mental model.
I know what AI tools our organisation has already licensed or approved for use.
Using unapproved tools creates compliance and data security risk.
I have tried at least one AI tool personally for a work task.
First-hand experience matters. You can't lead adoption of something you've never used.
Our organisation has a position (even informal) on AI use in the workplace.
No policy often means no permission — which creates hesitation and inconsistency.
I have budget, or can allocate budget, to improve a process that's costing us time.
Time savings = money. Being able to quantify the problem makes budget conversations easier.
I have the authority to approve a pilot or trial — or direct access to the person who does.
AI adoption without a decision-maker in the room usually goes nowhere.
Your Score
0
out of 18 checked
17–18 ✓
Strong foundation. You're well-positioned to start. Book an audit to identify your highest-impact opportunities.
11–16 →
Some gaps to address. Good base but specific areas need attention before you scale. An audit will show you where to focus.
6–10 !
AI adoption will be harder without some groundwork. Most gaps are fixable in 4–6 weeks with the right plan.
0–5 ✕
Not ready yet — and that's okay. Knowing this now is valuable. An audit gives you a clear, honest starting point.
Done — check your inbox.
Your score is on its way with a note on where to start.