Mist rising off still water at the edge of a dense treeline

Business practice

Shadow AI exposure.

Know exactly what your team is putting into AI tools, what client data went with it, and what to do about it this week.

You have not asked your team what they are using. Not because you do not care, but because you are not sure you want the answer.

The tools arrived without a decision. Someone tried one on a deadline, it worked, and it spread. Nobody filed a request, nobody signed anything, and the first time it becomes a subject is when a form asks whether your firm has a written policy. You suspect the honest answer and you would rather not put it in writing.

Two weeks from now that is no longer where you sit. You know which tools are in use, who is using them, and which categories of client data have passed through them. You have a short list you can act on immediately and one longer item that needs real work. The uncertainty is gone, and what replaces it is a decision you get to make on purpose.

The approach

Ask, map, then act.

Ask anonymously.

Nobody tells the owner they pasted a client file into a chatbot. They will tell an anonymous survey, and they do. The gap between what leadership believes and what the team reports is the finding, and it is almost always wider than expected.

Map the data.

A tool list is not exposure. Exposure is which categories of information moved into which tool, under whose account, and whether that vendor trains on what it receives. That mapping turns a vague worry into a specific, finite list.

Act this week.

Every exposure review ends with three things you can do immediately at no cost, and one thing that will still be there in six months if nobody owns it. Knowing the difference is most of the value.

The situation, in numbers

This is not a rare problem.

46%

Of US accounting firms have entered confidential client information into public AI services

63%

Of breached organisations had no AI governance policy in place

670k

Average dollars added to breach cost where shadow AI was involved

Sources: KPMG AI Adoption Across Finance Functions, 2025. IBM Cost of a Data Breach, 2025. Figures are industry research, not client results.

Mist rising off still water at the edge of a dense treeline

Recognise this

You already know the answer to one of these.

  • You could not name every AI tool in use in your firm today.
  • Nobody has ever formally approved a tool, and several are clearly in use.
  • Your insurance renewal or a client questionnaire has asked about AI, and the answer was uncomfortable.
  • Someone on your team is visibly faster than they were last year and you have not asked why.
  • You have thought about raising it in a meeting and decided the timing was never right.

The work

Four steps, about ninety minutes of your time.

The leadership conversation

Thirty minutes with the person who signs. Six questions covering what you believe is in use, what data touches it, who approved it, what happens when a key person is out, where work gets redone, and what you bought this year that nobody opens.

The anonymous team survey

Five questions, two minutes to answer, sent under your name. Anonymity is the point. This is where the accurate picture comes from, and it is the half of the exercise that cannot be replaced by an assumption.

The exposure map

One page, back within seventy two hours. Tools in use against tools approved. Data categories at risk. The specific places where a client confidentiality obligation and a free tool are currently in the same sentence.

The short list

Three actions you can take this week without spending anything, and one item that needs real ownership. Useful whether or not the conversation goes any further, which is how a diagnostic should be built.

Questions

Asked before, answered plainly.

Stop guessing what is in use.

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