Shadow AI has officially entered the enterprise

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AI tools have become a workplace staple, but their unsanctioned use has given rise to shadow AI. It refers to the untracked usage of any AI tools or applications without approval or overview of the information technology (IT) or security team. This is substantiated by the Verizon 2026 Data Breach Investigations Report (DBIR) which shows how rapidly the shadow AI trend is growing. The report states that 67% of users access AI services through non-corporate accounts on corporate devices, while 45% of employees regularly use AI tools, whether authorized or unauthorized. Notably, shadow AI has become the third most common non-malicious insider action found in data loss prevention (DLP) datasets, with incidents increasing fourfold from the previous year. Additionally, AI adoption among employees jumped from 15% to 45% in just one year.

These findings indicate that shadow AI is no longer just an IT policy violation. It has evolved into a data security and governance challenge that organizations cannot afford to ignore.

How ManageEngine Endpoint DLP Plus helps control shadow AI risks

As organizations embrace AI-driven productivity, they need solutions that can identify sensitive information, monitor data movement, and enforce security policies to govern confidential data and ensure it does not leave the organization. ManageEngine Endpoint DLP Plus provides the visibility and controls required to reduce shadow AI risks while supporting responsible AI usage.

Discover sensitive data before it is exposed

Organizations cannot protect information they are unaware of. According to the Verizon 2026 DBIR, source code was the most commonly uploaded data type to unauthorized AI systems, followed by research materials, technical documents, and business data. Endpoint DLP Plus helps security teams discover and classify sensitive data across managed endpoints, making it easier to identify confidential data before it is exposed to AI platforms. With comprehensive data discovery and classification capabilities, organizations can:

  • Define and identify sensitive files and regulated data using predefined and custom rules and templates.
  • Discover intellectual property and business-critical information.
  • Protect source code and proprietary information from unauthorized exposure.
  • Classify structured and unstructured data.
  • Map sensitive information across endpoints and user environments.

Monitor data movement to AI applications

One of the biggest challenges with shadow AI is the lack of visibility into how employees interact with AI tools. Endpoint DLP Plus helps organizations monitor data movement and understand when sensitive information is being transferred to the external environment. Security teams can:

  • Gain visibility into file uploads and transfers.
  • Monitor web-based interactions involving sensitive data.
  • Track movement of confidential information across endpoints.
  • Gather details of complete data movement trail.
  • Identify potentially risky user activity involving AI applications.

Prevent unauthorized data sharing

Visibility alone is not enough. Organizations also need the ability to prevent sensitive information from reaching unauthorized destinations. Endpoint DLP Plus enables organizations to:

  • Block uploads of sensitive content to unauthorized applications and services.
  • Restrict data transfers to unapproved cloud destinations.
  • Block uploads and copy-pasting of PII to GenAI platforms such as ChatGPT, Gemini, and Claude.
  • Track and monitor sensitive data shared via email channels.

Taking control of shadow AI

Shadow AI has quickly evolved from a productivity trend into a significant data security concern. The Verizon 2026 DBIR highlights unauthorized AI usage as a growing insider-related risk, with employees increasingly sharing source code, customer information, research materials, and business documents with AI tools. As AI adoption accelerates, organizations need greater visibility and control over how sensitive data is being used and shared.

The goal is not to block AI development, but to enable its usage securely. By combining clear AI usage policies with data discovery, upload monitoring, insider risk detection, and policy enforcement, organizations can reduce Shadow AI risks without impacting productivity. ManageEngine Endpoint DLP Plus helps businesses embrace AI while maintaining control over sensitive data, compliance requirements, and intellectual property.