AI for Business
What’s shadow AI?
Shadow AI is employees using AI tools the business hasn’t approved. It’s already happening in many Australian businesses, and the usual response makes it worse.
Shadow AI is the use of artificial intelligence tools inside a business without the knowledge or approval of the people responsible for the business. A commercial manager pastes a customer contract into a free AI tool to summarise it. An analyst uploads a cost file to get help with a formula. A sales manager drafts a tender response in a browser tab on a personal account. None of it appears in any company system, and none of it was reported to anybody.
It’s common. In the University of Melbourne and KPMG’s 2025 study of trust in AI, 48% of Australian employees who use AI said they had used it in ways that contravene company policy, including uploading sensitive company information into free public AI tools.
The term borrows from shadow IT, which described the same pattern with software. Somebody needed a tool, the company didn’t provide one, and they found their own. Shadow AI moves faster than shadow IT ever did, because there’s nothing to install, nothing to buy and nothing for anybody to approve.
Why capable people do it
The uncomfortable part of shadow AI is that it’s usually done by good employees doing their jobs well. Public AI tools are genuinely useful. They summarise a forty-page agreement in seconds. They turn rough notes into a readable board paper. They explain a clause. They draft the first version of something that would otherwise have taken a Sunday.
When a business provides no alternative, the choice an employee faces is between doing the work well and following a policy they may not have read. Most people, most of the time, choose the work.
Often there’s no policy to read. The same study found only 30% of Australian employees say their organisation has a policy guiding generative AI use, and 60% admit they have hidden their use of AI at work.
Shadow AI isn’t an employee discipline problem. It’s a tooling gap that employees are solving on their own.
What’s actually at risk
The risk is rarely dramatic. It’s the steady, unrecorded movement of information out of the business and into a service the business has no relationship with.
- Customer pricing and margin detail, pasted in to be analysed
- Contract terms and correspondence, pasted in to be summarised
- Cost models and supplier rates, uploaded for a calculation
- Board material and strategy documents, uploaded for a critique
- Employee and remuneration information, pasted in to be reworded
Two things follow. The first is that the information is now outside your control, and depending on the tool and the account type it may be retained or used to improve the provider’s models. The second is quieter and often worse: there’s no record. If a customer or an insurer asks what was disclosed and when, the honest answer is that nobody knows.
For personal information, the Office of the Australian Information Commissioner (OAIC) is blunt. Once it goes into a generative AI product, “it will be very difficult to track or control how it is used, and potentially impossible to remove the information from the system”.
How to tell whether it’s happening
Shadow AI leaves almost no trace in company systems, because it happens in a browser on an account the company doesn’t own. Network logs catch some of it and miss the rest, particularly anything done on a phone. In practice the signs are behavioural.
- Written work that has improved noticeably in quality without a corresponding change in time available
- Long documents summarised faster than anyone could have read them
- Analysis presented without working, where working used to be shown
- People asking whether a particular tool is allowed, which usually means it’s already in use
Why banning it doesn’t work
The instinctive response is a policy that prohibits public AI tools. Policies are worth having, and a business should be able to say what is and isn’t acceptable. But a ban on its own has a predictable effect: the behaviour tends to move to personal devices, where the business can see even less of it, and the people most likely to comply are the ones who were least likely to be a problem.
A ban also asks employees to be less effective on purpose. That’s a difficult thing to ask, it’s harder to sustain, and it puts the business in the position of having removed a capability its competitors are using.
A policy is useful. A practical alternative is better.
What actually works
Shadow AI stops being a problem when the approved tool is better than the unapproved one for company work. That’s achievable, because a public AI tool has a structural disadvantage on exactly this kind of work: it doesn’t know anything about your business.
A public model can explain a contract clause in general. It can’t compare the clause with your standard terms, because it has never seen them. It can describe how manufacturers usually think about changeover cost. It can’t tell you what yours is. A private AI environment that holds approved company information answers the specific question, which is the question people actually have.
Three things need to be true for people to move across. The approved tool has to be at least as good at the work. It has to be as easy to reach: a login and a browser, with no request form. And the business has to say clearly what it’s for, because employees who have been quietly using AI for a year won’t volunteer that on day one.
A reasonable position for an Australian business
- Assume it’s already happening, and stop treating the question as hypothetical
- Write a short policy that names what must never go into a public tool, in plain terms
- Provide an approved alternative that works on company information, inside your own controls
- Say publicly that the alternative exists, and let people admit what they were already doing
- Keep a person accountable for the output, whichever tool produced it
It lines up with the National AI Centre’s guidance for AI adoption, which includes making a senior leader the owner of AI governance and having an AI policy that tells staff about AI risks and how to manage them.
The goal isn’t to stop people using AI. Most of the value they’re getting from it is real. The goal is to make sure the useful thing happens somewhere the business can see it.
Sources
- University of Melbourne and KPMG, Trust, attitudes and use of artificial intelligence: A global study 2025, Australian story, 2025
- OAIC, Guidance on privacy and the use of commercially available AI products, 2024
- National AI Centre, Guidance for AI adoption: foundations, 2026
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