Artificial Intelligence as an Insider Risk
Artificial intelligence (AI) tools have moved quickly from a technological novelty to standard tools of the workplace. They draft and summarize documents, clean up data, answer routine questions, and take on the administrative work that used to consume staff hours. For most organizations, using them is no longer an edge, but the standard. As a result, choosing not to use them carries its own cost, because competitors who do adopt them work faster and at lower cost. However, the same tools also open a new way for sensitive information to leave the organization, not through an attacker but through an employee typing the wrong thing into a prompt. This week's MMR looks at how AI becomes an insider risk, and at the small number of things that should never be entered into a public tool.
The Productivity Case and the Catch
The case for adopting AI is strong. Used well, these tools cut down on mundane work, shorten turnaround on routine tasks, and free staff to spend their time on judgment rather than formatting. An organization that refuses to use them is accepting a disadvantage against competitors who are moving faster. At this point, treating AI as something to be banned outright is a vulnerability in itself.
The catch is that the same feature driving the productivity is also the source of the risk. These tools are useful because a person can hand them real material and get real work back. That means employees paste in actual documents, client information, and internal detail, and every one of those inputs leaves the organization's control the moment it is submitted.
How the Exposure Happens
The scale of this is now measurable. A 2026 analysis by the security firm Cyberhaven found that 39.7 per cent of the information employees enter into AI tools contains sensitive data, up sharply from earlier years. Separate figures show that most enterprise users paste content into AI prompts many times a day, and that a meaningful share of those pastes carry personal information, customer records, or internal strategy. Much of this happens through personal accounts on public tools rather than sanctioned corporate systems, which is where the exposure is greatest.
The clearest cautionary case is Samsung. In May 2023, the company found that staff had entered confidential material into a public AI tool on at least three occasions within about three weeks, including source code and the recording of an internal meeting. Samsung's concern was that information sent to these tools can be stored on outside servers, is difficult to retrieve or delete, and can surface later in ways the company cannot control. It responded by banning generative AI on company devices. The point is that ordinary, well-meaning use can move protected information outside the organization in seconds, with no attacker involved.
What This Means for Businesses Across Sectors
This applies to every sector, because every organization holds information that should never be entered into a public AI tool. "Off-limits" information includes the full names, addresses, and contact details of clients, staff, or members of the public; financial and account information; medical or other regulated personal records; and sensitive internal material such as security arrangements, legal strategy, unreleased deals, or proprietary methods. Entering any of these into a consumer tool can breach privacy obligations, contractual commitments, and in some cases the law, regardless of the employee's intent.
The practical response is discipline rather than prohibition. Organizations that handle this well give staff sanctioned tools with proper data handling, set clear rules on what may and may not be entered, and make the distinction between public and enterprise systems part of routine training. The aim is to keep the productivity while removing the specific categories of information that create exposure.
The Role of Digital Investigative Intelligence
Digital investigative intelligence has a specific role here, which is to show an organization what of its information is already exposed. The same open-source techniques used to assess an external threat can be turned inward to find where sensitive corporate or personal data has surfaced online, whether through AI-related leakage, a breach, or careless posting. That gives security and legal teams a factual picture of their external footprint rather than an assumption about it. Ongoing monitoring also flags when protected information appears where it should not, so the organization can act before that exposure is found and used by someone else.
Conclusion
Artificial intelligence is now part of how competitive organizations operate, and avoiding it carries a real cost. Convenience, though, comes with exposure, and that exposure grows every time sensitive information is entered into a tool the organization does not control. The organizations that manage this well are the ones that adopt AI deliberately, draw a clear line around the information that must never go into it, and keep in view that a single prompt can undo years of careful data protection.
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