Shadow AI tools: managing risk without banning everything
How companies can manage the risks from employees' unsanctioned use of AI tools - without making a blanket ban the only answer.
Since 2023 I have noticed a consistent pattern in conversations with clients: in virtually every company, employees are using AI tools that have not been approved by IT or security. ChatGPT, Claude, Copilot, dozens of specialised tools for specific tasks. Some people use them for writing emails, some for analysing data, some for writing code.
This is the classic shadow IT pattern - but with a fundamentally different risk profile.
Why AI tools are a special case
Shadow IT has always existed. Employees installed unapproved software, used personal services for work tasks. The risk was usually contained: an unsanctioned messaging app or file-sharing service is bad, but manageable.
With AI tools the picture is different for several reasons.
First - data leaves for processing. When an employee pastes a contract fragment, a client list, or internal analytics into ChatGPT, that data is processed on a third-party provider's servers. Terms of service vary across services, as do data storage and usage policies.
Second - scale. This is not one employee with an unapproved app. It is dozens or hundreds of employees sending pieces of corporate context into different external systems, daily.
Third - pace of growth. Six months ago there were fewer such tools and they were less convenient. Today they are embedded in browsers, mail clients, and office applications. Tomorrow there will be more.
Why banning does not work as an answer
The most intuitive security response is to block. That is logical: no tool, no risk. But there are several problems with that logic.
First - it is technically difficult. Blocking a specific site is straightforward. But AI capabilities are being built into already-permitted tools: Microsoft 365, Google Workspace, browsers. Full blocking requires significant ongoing effort.
Second - employees will work around it. If an AI tool provides real productivity value, a ban creates motivation to bypass it through personal devices or personal accounts. The risk does not disappear - it becomes less visible.
Third - competitive cost. Companies that allow conscious use of AI get real productivity benefits. A blanket ban is a choice to prioritise security at the cost of effectiveness.
A managed approach
Instead of banning, it makes sense to build a managed policy:
Classify your data. Understand which data is sensitive and should not leave the perimeter: customer personal data, financial details, trade secrets, open deals. This is a specific list, not "anything business-related."
Define permitted tools. For general tasks - drafting text, editing, looking things up - choose one or two tools with acceptable data processing terms and give employees a legitimate, convenient path.
Train, do not only prohibit. Employees should understand what specifically cannot be sent to AI tools and why. That is more effective than a list of blocked sites.
Create an escalation path. If an employee sees potential value in a specific tool, there should be a simple way to request its review and approval.
Questions to assess the current situation
- Do you know which AI tools employees are using today?
- Does the company have an AI tool usage policy - written and understandable?
- Do employees know which data cannot be sent to third-party AI services?
- Do you have a corporate AI tool option that covers the main needs?
- How would you know if significant company data leaked through an AI tool?
Shadow AI tools are not a security problem to be defeated. They are a reality to be managed.