An employee needs to quickly analyze a spreadsheet, prepare a business proposal, or summarize a lengthy document. They open their favorite AI tool, upload the necessary files, and have the results within minutes. The task is completed much faster, but the company’s IT department has no idea which tool was used or what information was shared with it.
Situations like these are behind the growing phenomenon known as Shadow AI, the use of unapproved artificial intelligence tools outside a company’s controlled IT environment. Although employees are usually simply trying to get their work done faster, this behavior can introduce security and operational risks for their employers.
As AI tools become increasingly accessible, companies face a growing challenge: allowing employees to benefit from new technologies while maintaining control over corporate data and internal processes.
Companies Are Losing Visibility into the AI Tools Employees Use
While IT departments have traditionally managed the introduction of enterprise software, almost any employee can now create an account with a publicly available AI service and start using it for work within minutes.
According to The State of AI 2026, a study conducted by Osterman Research for AvePoint, the share of organizations unable to determine whether employees use unapproved AI tools increased from 6.3% in 2025 to 17.6% in 2026. The survey included 750 senior professionals responsible for information management, data security, and corporate AI programs.
Another perspective comes from the Netskope AI Report 2026, which draws on operational data from customer organizations. According to the report, 56% of monitored AI users rely exclusively on company-managed applications, while 30% use only personal accounts and another 14% combine both approaches.
Using a personal account does not automatically mean violating company policies. However, these findings illustrate how much AI-related work may take place outside centrally managed environments, where organizations have greater control over access permissions and the handling of information.
Why Do Employees Turn to Unapproved AI Tools?
Using unapproved AI tools does not necessarily mean employees are trying to hide something or deliberately break the rules. Often, they are simply looking for the easiest way to complete a task, using technology they are already familiar with.
A marketing specialist needs to prepare campaign materials, an HR professional wants to process job applications, and a sales team needs to analyze customer data. If approved corporate tools lack the necessary features or are too complicated to use, employees may turn to more accessible alternatives.
Poor communication can also contribute to the problem. Some employees simply do not know which AI services they are allowed to use, what information they can share, or whether approval from the IT department is required.
The growing use of unapproved AI tools can therefore reveal weaknesses in internal processes or unmet employee needs. Management should look beyond which applications people are using and try to understand the specific tasks these tools help them accomplish.
The Biggest Risks Arise When Handling Sensitive Company Data
Using public AI services is not inherently unsafe. The risks depend primarily on what information employees share, how the provider handles that information, and whether the company has assessed and approved the relevant data processing conditions.
Consider a sales representative who uploads a spreadsheet containing customer contacts, negotiated prices, and sales figures to a personal AI account. Their intention is simply to prepare a quick report for management, but they may have shared confidential business information with an external service whose security practices the company has never reviewed.
According to the Netskope AI Report 2026, monitored organizations recorded an average of 69 incidents per week involving data being sent to AI applications in violation of established security policies, compared with 44 a year earlier. These figures represent detected policy violations, not confirmed data breaches.
Beyond personal and commercial information, sensitive materials may include internal documents, source code, or access credentials. The level of risk varies depending on the service, its configuration, and contractual terms.
The quality of AI-generated outputs presents another concern. If an employee uses AI to analyze financial data or prepare a customer proposal and passes the results along without verification, inaccuracies may influence business decisions or communication with customers.
Companies should therefore establish who is responsible for reviewing AI-generated outputs and for decisions made using that information.
Is Banning Unapproved Tools Enough?
A blanket ban on unapproved AI tools may be justified in certain environments, particularly when a company handles highly sensitive information. However, if employees have no practical alternative, restrictions alone may not address the reasons they started using external applications in the first place.
Some activities may simply move to personal accounts or devices, leaving the organization with even less visibility into how its information is being processed.
A more practical approach begins with understanding which AI tools employees actually use and why. Companies can then assess their security, establish clear policies, and offer approved alternatives that meet real workplace needs.
Employees also need straightforward guidance on what data they can share with AI, when approval is required, and how to verify the results. These rules should be specific enough to apply in everyday situations, rather than existing only as part of mandatory training.
AI education also has a regulatory dimension. Article 4 of the EU AI Act requires providers and organizations deploying AI systems to take measures to ensure an appropriate level of AI literacy among people working with those systems. The measures should reflect their experience, responsibilities, and the context in which AI is used.
Shadow AI Can Reveal Opportunities for Automation
Discovering that employees use unapproved AI tools does not have to be entirely bad news. It may also reveal tasks that consume unnecessary time and for which the company has yet to provide an effective solution.
For example, if several employees regularly use AI to process orders, analyze documents, or prepare reports, it may be worth examining the entire workflow. A shared solution connected to internal systems could prove more efficient than allowing everyone to develop their own way of working.
This requires understanding how individual processes operate, where they obtain information, and what causes unnecessary delays. Only then can a company determine whether it needs an approved AI tool, a custom automation, or changes to an existing process.
We take a similar approach to AI transformation at Techmates, starting with an analysis of how work is actually performed and identifying opportunities for measurable improvement.
How Can Companies Regain Control?
The first step should be an open assessment involving IT, management, and employees themselves. Companies need to understand which applications are being used, what information they process, and how they help people in their daily work.
Based on these findings, organizations can establish appropriate security policies, assign responsibilities, and decide which tools to approve. Regular reviews are equally important, as new AI services and integration possibilities continue to emerge.
The greatest risk arises when companies lose visibility into the technologies being used and cannot determine how their data is handled. Employees will continue exploring new tools, especially when those tools help them work faster.
Organizations that combine secure AI adoption with their employees’ actual needs can turn individual experiments into opportunities to improve internal processes and introduce automation in a more structured way.