Shadow AI Use in the Workplace: How to Detect It and Reduce Risks

Detecting and managing shadow AI in the workplace

Many businesses are experimenting with artificial intelligence (AI) tools to improve decision-making, increase efficiency, and drive innovation and growth. However, a troubling trend in AI use, known as shadow AI, has emerged. It poses significant security risks, including data leaks and compliance violations.

Shadow AI refers to employees using an AI tool or application, such as ChatGPT or Claude, without approval or oversight by the organization’s IT department or security team. It typically occurs when an employee uses a free or self-purchased AI tool for work-related tasks, such as creating content, analyzing data, or writing code.

Let’s take a look at these risks and how your business can develop a robust AI-use strategy to address them.

Why Do Employees Use Shadow AI?

Employees use unauthorized AI tools to work faster or more effectively. They often turn to these tools when frustrated by their organization’s lack of AI tools or when employer-provided AI tools don’t have the functionality needed for their tasks.

For example, a developer could use Google Gemini Code Assist to speed up a coding project, potentially revealing internal proprietary code. A designer may turn to an AI image tool to create visuals for a marketing campaign but fail to check with legal to confirm commercial usage rights. A sales rep could use ChatGPT to summarize an internal document before sharing the summary with a potential customer. If the document contains sensitive business information, ChatGPT’s servers will capture its contents when the rep uses the document’s text in prompts to generate the summary.

How Prevalent Is Shadow AI?

A 2025 study found that AI-driven tools are now the most common unmanaged software applications used by employees. Employees use these tools to automate tasks, draft emails, analyze data, create presentations, or complete other tasks.

The use of shadow AI introduces unique risks due to how AI models handle data, generate outputs, and influence decisions. Employees are often unaware that they may be exposing sensitive data to third parties.

Several factors are driving the surge in shadow AI. Many organizations have prioritized digital transformation, and this push has normalized the rapid adoption of new tools, often outpacing security oversight. The rise of free, user-friendly online GenAI platforms and affordable AI-driven SaaS applications offers easy access to AI tools. Employees often adopt these tools without involving their company’s IT team or considering cybersecurity risks.

What Are the Security Risks of Shadow AI?

The use of shadow AI introduces a variety of security risks. The top risks are:

Unnoticed data breaches.

A potential data leak occurs whenever an employee writes a prompt or query or uploads data to an unauthorized AI tool. That’s because many of these tools store inputs or metadata. If an employee discloses sensitive business information while using an AI tool, that information may be exposed to third parties. The AI tool could even use the information to train models that competitors use.

Detrimental influence on business decisions.

Because AI tools’ outputs are based on their training data, AI results can be inaccurate or biased. Employees may be making decisions based on models generated by corrupted or incomplete data. The output also may not align with a company’s objectives or policies.

Regulatory violations.

Shadow AI use can easily bypass internal data governance and privacy policies designed to ensure compliance with HIPAA, GDPR, and other regulations. Violations of these regulations can result in substantial fines and reputational damage.

Security vulnerabilities.

Unauthorized connections to external AI platforms increase the number of potential entry points for cyberattacks. These tools often have unsecured APIs and unmanaged integrations, and they’re sometimes accessed with personal devices. When employees use shadow AI tools, IT teams have no visibility into these activities, making security monitoring impossible.

How Can a Business Manage Shadow AI Risks?

Shadow AI is a trend that will continue to grow.  For small and medium-sized businesses, addressing the risks doesn’t require a massive budget or a large IT team. Following these steps will help you build a practical AI governance framework:

1. Conduct an AI audit. Survey employees about the AI tools they use and access that are connected to sensitive data or IT systems.
2. Establish a clear AI usage policy. Define which tools are approved, specify what data employees can share with AI tools, and indicate the consequences of noncompliance. Keep the language simple and accessible. Address violations consistently.
3. Make approved tools easy to use. If sanctioned AI solutions are harder to use than unofficial ones, employees will turn to unauthorized tools. Adopt tools appropriate for your staff and provide adequate training.
4. Train your staff. Help employees understand why your AI security guardrails exist. A culture of awareness is the best long-term defense.
5. Monitor AI use. Use network monitoring tools to detect and prevent unauthorized AI usage. The latest data loss prevention (DLP) tools address shadow AI risks by inspecting and filtering sensitive information to avoid data breaches.
6. Revisit your policy regularly. The AI landscape evolves fast. Schedule quarterly reviews to keep your policies up to date.

Sensible oversight of AI use doesn’t reduce efficiency or slow down innovation. It creates guardrails that enable employees to use AI confidently and securely.

Bring AI Use out of the Shadows

The use of shadow AI spreads when employees see easier ways to tackle everyday business challenges. The use of these hidden tools compromises IT security, risks compliance violations, and can lead to inaccurate or biased outcomes. However, a 2025 study found that although 68% of organizations have experienced data leaks linked to AI tools, only 23% have adopted AI governance policies to address the security risks.

By adopting AI-use policies and training your staff to remain vigilant about security risks when using AI tools, you can protect data and sensitive business information while still taking advantage of the many benefits of AI. Proactive governance today means fewer costly incidents in the future. If you have concerns about your business’s vulnerability to shadow AI, contact us today to speak to an IT security expert or to request a free network security assessment.