Your workforce is already using AI. Can you see it?

Most organisations did not decide to adopt AI. Their people did.

Somewhere along the way IT approved an assistant, wrote a policy, and moved on. Meanwhile the finance team found a tool that summarises board packs, someone in engineering installed a coding assistant, and a project manager connected an agent to the shared drive because it saved an hour a day. None of it went through a ticket.

This is shadow AI: AI tools in use across your organisation that nobody approved and nobody can see. It is not a story about staff behaving badly. People are using AI because it makes them faster, and that is exactly what you want. The problem is that nobody can see it, so nobody can make a sensible decision about it.

What shadow AI actually looks like

When an organisation runs AI discovery, the approved assistant is rarely the interesting part. What turns up usually falls into four groups.

Personal accounts. Staff signed up to a free or personal tier with their own email address. Whatever they paste in sits under terms your organisation never agreed to, and leaves with them when they do.

Browser extensions. Writing helpers and “summarise this page” tools that can read everything in the browser tab, including your internal systems.

AI inside software you already pay for. Vendors are switching AI features on inside platforms you licensed years ago. Often the first anyone hears of it is a release note.

Agents connected to your systems. This is the one that matters most. An agent given access to a mailbox, a file store or a ticketing system acts with that person’s permissions. If it can create and delete as well as read, a misunderstanding or a malicious instruction can do real damage, and it looks like ordinary authorised activity the whole way.

Why blocking it does not work

The reflex is to block AI at the firewall and be done with it. In practice that pushes usage onto personal phones and home laptops, where you have no visibility at all, and it costs you the goodwill of the people trying to work smarter. You also lose the productivity gains that made the tools attractive in the first place.

The goal is not zero AI. It is AI you can see, with sensible limits where the risk is real.

Five questions visibility should answer

If you cannot answer these today, that is the gap.

1. Which AI tools are in use, by person and by team?
2. Corporate or personal accounts? A work sign-in can be governed. A personal one cannot.
3. What data is going in? Customer records, financials, source code, legal advice?
4. Which agents can touch which systems, and can they only read, or also change and delete?
5. Who decides whether a new tool is allowed, and how quickly?

A practical way to start

Take an inventory. You cannot govern what you have not found. A lightweight discovery across your managed devices gives you a real list in days, not a guess from a staff survey.

Sort what you find. Most tools fall into three buckets: approved, tolerated with conditions, and not allowed. Keep it short and explain the reasoning, so people follow it.

Write a policy people can actually use. One page: an AI acceptable use policy covering which tools are approved, what must never be pasted into any of them, and how to ask for something new.

Put controls where the risk is. You do not need to inspect every prompt. Focus on sensitive data leaving the organisation and on agents with write access to core systems. Allow reading, restrict changes, and log what happens.

Review it monthly. New tools appear constantly. A monthly look at what has changed keeps the picture current without turning into a project.

The Australian angle

If staff put personal information into AI tools, your obligations under the Privacy Act still apply. The OAIC’s guidance on privacy and the use of commercially available AI products is worth a read, as is ASD’s Engaging with artificial intelligence. Both come back to the same point: you need to know what is being used and what is going into it. For the wider picture on protecting AI systems themselves, see our earlier post on securing generative AI.

Frequently asked questions

What is shadow AI? Any AI tool, account, extension or agent used for work without the organisation’s knowledge or approval. It includes personal accounts on approved tools, not just unapproved tools.

Is it a privacy problem if staff paste information into AI tools? It can be. If personal information goes into a tool your organisation has not assessed, your Privacy Act obligations still apply to how that information is handled and protected.

How do I find out which AI tools my staff are using? Run a discovery across your managed devices. Network logs and staff surveys miss personal accounts, browser extensions and AI features inside existing software. Device-level discovery finds them.

Should we just block AI tools? Usually not. Blocking pushes usage onto personal devices where you lose visibility entirely. Most organisations get better results from approving a small set of tools, protecting sensitive data, and restricting what connected agents can change.

How we can help

Our managed AI security service starts with finding out what is actually running, and that part costs nothing.

• Discover, free. A lightweight script through your existing management tooling. No agent, no endpoint install. You get an inventory of the AI applications in use.
• Trial, free. 30 days monitor-only with a scoped group. Nothing is blocked and nothing changes for your users.
• Review, free. We walk you through what your people are using, which accounts are personal, and where data is going. If it is not useful, we stop there.
• Govern, if you want to. Policy, data protection and agent controls, run month to month. You choose how much of the running you hand to us.

Perth-based, senior people.

If you would like to see what your workforce is really using, get in touch or email connect@summitcybergroup.com.au.