Shadow AI: What It Is, Its Risks and How to Control It

In recent years, artificial intelligence tools have become as easy to reach as a search engine. In seconds, an employee can ask an AI assistant to summarise a contract, translate an email, write a snippet of code or draft a reply to a client. The time saved is real. The problem appears when this happens outside any rules and without the company knowing. This is the phenomenon known as Shadow AI.

The term comes from the same family as "Shadow IT" — the use of apps and services not approved by the IT department. The difference is that AI tools are even easier to access, and the data they receive can be retained, processed or even used to train the models. In other words, the stakes are higher.

What Shadow AI actually is

Shadow AI means using, for work, AI tools that the company has not approved, has not assessed and cannot see. A few common examples:

• An employee pastes a contract or a table of client data into a public AI assistant to get a summary.
• Someone in sales runs a list of prospects through AI to draft personalised messages.
• A developer asks an assistant to fix a bug and feeds it snippets of the company's internal code.
• A colleague in HR translates or rewrites a document with employee data using a free service.

In all these cases the intent is usually good: people want to be faster and more efficient. That is exactly why Shadow AI is not solved through blame, but through clear rules and training.

Why it appears

The phenomenon is not a whim, but the natural response to three realities:

• Productivity pressure. Everyone has to do more, in less time. AI looks like the simplest shortcut.
• Tools within anyone's reach. Many AI services are free, accessible from the browser, with no installation and no approval.
• No official alternative. When the company does not provide an approved tool and clear rules, employees pick their own.

The real risks

Shadow AI is not dangerous because AI is "bad", but because using it without control creates exposures the company cannot even see.

• Leaking confidential and personal data. Data entered into a public tool can be kept on servers outside the company's control. If it is personal data, GDPR comes into play; if it is client information, confidentiality contracts may be breached.
• Use for training the models. Some services may use what you enter to improve their models, which means your information can indirectly end up in answers given to other users.
• Decisions based on incorrect results. AI tools can "invent" information that looks correct. Used without checking, it can lead to mistakes in offers, documents or analyses.
• Intellectual property. Generated content can raise questions about who owns it and whether it can be used commercially.
• Lack of visibility. The biggest risk of all: you cannot protect, assess or fix something you do not even know is happening in your company.

On top of these comes a shifting context: the European Artificial Intelligence Regulation (AI Act) is gradually introducing obligations around the responsible use of these technologies. We also wrote about how AI adoption ran ahead of the rules in the article on AI adoption outpacing governance.

How to keep it under control

The good news is that Shadow AI can be solved without stopping innovation. A total ban almost never works — employees will use these tools anyway, just more quietly, and you lose all control. The healthy approach has a few steps.

• Gain visibility. Find out which AI tools are already in use in the company and for what. You cannot manage what you do not know.
• Provide approved alternatives. Offer one or two assessed tools, preferably with guarantees that data is not used for training, so people no longer turn to uncontrolled options.
• Classify the data. Make it clear which information may never be entered into a public AI tool (personal data, client data, trade secrets).
• Train your people. Most slip up out of not knowing, not out of bad intent. Training turns the risk into a healthy habit.
• Monitor in moderation. Check usage within reasonable, transparent limits, not in secret, just like any other security policy.

These steps rest on the same foundation as everything else: a healthy security culture, where people know what is allowed and why.

What management must do: an AI policy and a procedure

Here we reach the conclusion that matters most. The responsible use of AI tools cannot rely on each person's common sense. It has to start from the top, from leadership, in the form of written rules.

Awareness of AI tool use should be mandatory for all employees, regardless of department or role. Everyone uses, or will use, these tools — so everyone needs to know how to do it safely.

In addition, every organisation should have a management AI policy and a procedure that explain, clearly and in plain terms:

• Which AI tools are allowed — the list of those approved and assessed by the company.
• How they may be used — under what conditions, with which accounts, with what privacy settings.
• For what purposes — which tasks are suitable and which remain solely in human hands.
• What limitations apply — which data may never be entered, which decisions cannot be left to AI, and what must always be checked by a person.

Such a policy, paired with training, turns Shadow AI from a hidden risk into an open, controlled and safe use of a technology that, used well, genuinely helps.

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