Artificial intelligence is quickly becoming a daily productivity tool in the workplace. Employees are finding new ways to use AI to work faster like summarizing documents and analyzing data, but there’s a growing problem many businesses don’t realize they have yet: Shadow AI.

Shadow AI introduces serious security, compliance, and data exposure risks without leadership or IT teams even knowing.

What is Shadow AI?

Shadow AI refers to employees using AI tools or applications without approval or visibility from IT or security teams. Employees adopt AI into their work to improve productivity or automate tasks, but bypass company policies, security controls, and data protection standards.

Common examples of shadow AI include:

• Uploading internal or confidential documents into public AI tools
• Using AI browser extensions or plugins with approval
• Creating AI-powered apps or automations connected to work data

This issue is far more widespread than you may realize. According to Grip’s 2025 SaaS Security Risks Report:

• 91% of AI tools used by employees are not monitored by IT or security teams
• AI adoption is outpacing security governance by a 4:1 margin
• Over 95% of organizations show ChatGPT usage, even in banned environments — indicating widespread workarounds and unapproved use.  

The Security Risks of Shadow AI

Unapproved AI tools create several risks for businesses including:

1. Data Leaving Approved Systems: When employees paste information into AI tools, that data leaves the company’s secure environment. This can lead to compliance violations, data ownership concerns, and loss of control over sensitive information.
2. Exposure of Sensitive or Regulated Data: Prompts, uploads, and conversations may include client data, financial information, intellectual property, or internal strategy. It may be stored or reused outside your organization.
3. Increased Operational Risk: AI tools can influence decisions, automate processes, or generate content that impacts business operations, often without validation, oversight, or accountability.

Identity and Access Risks

One of the most overlooked dangers of shadow AI is identity and access control. These tools introduce:

• Unmonitored user accounts created outside your single sign-on (SSO) system, preventing IT from managing or disabling access
• Over-permissioned access, where apps receive more access to systems or data than necessary
• Long-lived permissions and tokens, allowing access to remain active long after it should be removed
• Data stored outside approved systems, with AI tools retaining files, outputs, and generated content beyond company control

Together, these issues create blind spots that traditional security tools may never detect.

Impact on Businesses

The Cloud Security Alliance found that one-third of companies experienced a cloud data breach involving an AI workload. Of those incidents:

• 21% were caused by vulnerabilities
• 16% by misconfigured security settings
• 15% by compromised logins or weak authentication

How Businesses Can Manage Shadow AI Risks

Businesses should focus on responsible and secure AI usage with a combination of practical approaches.

Develop a flexible governance framework: Employees need clear guidance on how AI can be used safely. A flexible AI governance framework helps define approved tools, acceptable data use, and expectations for oversight without slowing productivity.

A strong framework should clearly outline:

• What types of data can and cannot be shared with AI platforms
• Which AI tools are approved for business use
• How AI-generated information should be reviewed before being used or shared

When these boundaries aren’t defined, employees create their own rules, which is exactly how shadow AI grows. We’ve outlined key workplace guidelines and practices that help businesses minimize risk while using AI responsibly. 

Implement technical guardrails: Policies alone aren’t enough. Technical guardrails act as a safety net by controlling access and permissions, enforcing authentication standards, and preventing sensitive data from being shared externally.

Monitor AI usage: You can’t protect what you can’t see. Visibility into AI usage is critical to identifying shadow AI early.

Emphasize collaboration: Open communication reduces risky workarounds and builds trust between teams. Employees should feel comfortable asking questions about AI capabilities and limitations while IT teams gain better insight into which tools may be appropriate for the business.

Reiterate the risks: Ongoing education ensures employees understand why policies exist and how their actions impact security, compliance, and the business as a whole.

Businesses that succeed with AI are the ones that embrace innovation, set clear expectations, and balance productivity with security.

We can help

AI is becoming part of everyday work, but without visibility and clear guardrails, shadow AI can quietly introduce security and compliance risks. With the right policies and guidance in place, businesses can take advantage of AI without losing control of their data.

Not sure what AI tools are being used in your environment or how to manage them safely? Schedule your free assessment today to improve visibility and put practical safeguards in place. Getting ahead of shadow AI now can prevent costly issues later.