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AI Governance

Your employees are already using AI you did not approve

The AI question most business owners ask is which tool to buy next. The more urgent question is what tools are already running inside the business, and what data is going through them. A Cybernews survey of more than 1,000 US employees found that 59 percent use AI tools their employer never approved. Among executives and senior managers, that number reaches 93 percent. Three quarters of those employees admitted to sharing sensitive data with those tools. This is not an edge case. It is the default state of most businesses right now.

By Fabio Rabelo · Founder, ATLACIS ·

What two studies found

A Cybernews survey of more than 1,000 US employees, conducted in August 2025, found that 59 percent use AI tools at work that their employer never sanctioned. Among executives and senior managers, the number climbs to 93 percent. Three quarters of those employees admitted to sharing potentially sensitive information, including customer data, internal documents, and employee records, with those tools. A separate BlackFog study, based on a survey of 2,000 respondents conducted by Sapio Research in November 2025, found similar patterns. Eighty-six percent of employees use AI tools weekly for work. Nearly half (49 percent) use tools not sanctioned by their employer. Sixty percent say speed is worth the security risk. Roughly a third shared research or datasets, more than a quarter shared employee data, and 23 percent shared financial statements.

Why employees reach for tools the business never approved

The BlackFog research found that only around a third of employees using company-approved AI tools said those tools fully met their work requirements. When the approved option does not do what someone needs, they find one that does. Free versions of public AI tools are easy to access, require no procurement, and can be started in under a minute. The Cybernews survey found that 63 percent of employees believe it is acceptable to use AI when no company-approved option or IT oversight exists. Twenty-one percent think their employer will simply turn a blind eye as long as the work gets done. The result is a pattern where employees solve the immediate problem, and the business inherits a data risk it does not know about.

What data is leaving through these tools

The data employees share with unsanctioned AI tools is not limited to low-stakes material. The BlackFog study found that a third of employees shared research or data sets, more than a quarter shared employee information such as staff names, payroll, or performance data, and 23 percent shared financial statements or sales data with unapproved tools. The Cybernews survey found that customer contact data and internal documents are common. Fifty-one percent of BlackFog respondents admitted to connecting AI tools to other work systems or applications without IT approval. That means the exposure is not just one-off. It can be ongoing and connected.

The part that surprises most owners

What makes this difficult to surface is that it is often tacitly supported. The Cybernews survey found that 57 percent of employees using unsanctioned tools said their direct manager is aware of and supports the behavior. The BlackFog study found that 21 percent believe their employer will ignore it as long as the work is completed. This is not a rogue group of employees hiding something. It is a broad pattern of informal adoption that has moved faster than the business has moved to address it. An owner who believes they have no AI exposure often has significant exposure they simply have not been told about.

This is not the same risk as vendor access being restricted

The Anthropic model access story from last week illustrated what happens when an AI vendor you depend on becomes unavailable through an external decision you do not control. Shadow AI is a different problem. It is the risk that sits inside the business already, created by internal behavior rather than external decisions. One is about what happens when a vendor goes away. The other is about what is happening right now, quietly, inside the operation. Both matter and both require a response, but they require different responses.

Three things to do before spending on more AI

First, find out what is already being used. Ask your team directly. A short, honest conversation about which AI tools people are using for work will surface more than any technology audit. What you hear may surprise you. Second, set one clear data rule. Before the conversation can change behavior, employees need a simple and specific rule about what can and cannot go into AI tools. Not a long policy document. One clear line: for example, no customer data, no financial records, no employee data, no vendor contracts into any AI tool the business has not approved for those data types. Third, create a path to a better answer. If employees are reaching for unsanctioned tools because the approved options do not meet the need, that gap is the thing to close. Blocking access without addressing the underlying need pushes the behavior further into the shadows, not out of them.

The ATLACIS view

An owner who asks 'what AI tool should I buy?' is asking the right question at the wrong moment. The first question is 'what is already being used inside the business, what data is going through it, and is that acceptable?' That question is harder to ask because the answer might be uncomfortable. But it is cheaper to find out now than after an incident. Shadow AI is not a technology problem. It is an information problem: the people running the business do not have a clear picture of where AI sits inside the operation. Getting that picture is the starting point, not the destination.

The short version

  • A Cybernews survey found 59 percent of US employees use AI tools their employer never approved. Among senior managers, the figure is 93 percent.
  • A BlackFog study of 2,000 respondents found that 49 percent use unsanctioned tools, and 60 percent say speed is worth the security risk.
  • Data shared with these tools includes customer records, financial statements, employee data, and internal documents.
  • Many employees are not hiding it: most say their direct manager is aware and supports the behavior.
  • The first step is not buying a new AI tool. It is finding out what is already inside the business and setting one clear rule about what data may and may not go into any AI tool.
Tags:shadow AIAI governancedata exposureAI riskbusiness AI
FAQ

Common questions

What is shadow AI?
Shadow AI is AI used inside a business without the formal approval or oversight of the organization. Employees use tools to get work done faster, often without realizing the data risk or the lack of security controls on those tools.
How common is unauthorized AI use in the workplace?
A Cybernews survey of more than 1,000 US employees found 59 percent use AI their employer has not approved. A BlackFog study of 2,000 UK and US respondents found 49 percent use unsanctioned tools. Both studies found the behavior is widespread and that employees regularly share sensitive data through those tools.
What should a business owner do about shadow AI?
Start by finding out what tools are actually being used, through direct conversation with your team. Set one clear and simple rule about what data may not go into any unapproved AI tool. Then create a path to approved alternatives that actually meet the team's needs. Blocking without replacing just hides the behavior.

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