• Shadow AI is more than unsanctioned tooling—it’s unmanaged data movement at scale.
• Blocking generative AI stalls innovation, but ignoring it can expose sensitive data.
• Security teams need visibility, classification, and control to manage Gen AI risk.

Shadow AI—the unauthorized use of generative AI (Gen AI) tools—is creating a silent but significant risk for enterprises as decentralized adoption continues to spread. Every employee who haphazardly feeds proprietary code, customer lists, or financial data into a public Gen AI prompt becomes an invisible threat actor. What starts as an innocent, productivity shortcut becomes a new path for data exposure that traditional security models struggle to keep up with.

While blocking Gen AI entirely can stymie productivity and innovation (and let’s be honest, just isn’t reasonable), allowing unrestricted use all but guarantees that sensitive data will leave your organization. To manage Shadow AI effectively, organizations need a more intuitive, balanced approach. One that takes into account how Gen AI is actually being used, can contextually evaluate risk, and swiftly applies controls without disrupting operations.

Industry-leading Data Loss Prevention (DLP) solutions are designed with this in mind. A dynamic DLP tool will provide a three-stage strategy to data security that addresses both visibility and control challenges, allowing organizations to move beyond blanket bannings to implement a nuanced, fine-tuned approach.

Let’s take a closer look at each stage and its ideal outcomes.

A three-stage strategy to data security

Stage 1: Governance

Unearthing actionable visibility and insight

The challenge: You can’t control what you can’t see. One of the biggest hurdles security teams face is discovering who is using Gen AI, what sites they are visiting, and how much corporate data is potentially at risk. The volume and speed at which new Gen AI tools are adopted make this a never-ending cat-and-mouse game.

The solution: A top-tier DLP tool provides essential visibility into Shadow AI activity with: 

• Audit discovery. Audit functions as a powerful Shadow IT discovery capability, providing critical, real-time visibility into user activity across SaaS applications and websites. It tracks user details, overall usage, and key actions like uploads or downloads. This provides the granular data needed to identify which users and teams are accessing regulated Gen AI tools.
• Real-time site visibility. To address the gap between known apps and the constant launch of new Gen AI services, real-time visibility capabilities provide comprehensive insight into all traffic. Security teams can simply filter “generative AI” categories to quickly get a complete list of all Gen AI sites in use, along with org-wide usage metrics.
• Actionable reporting. Scheduled reporting capabilities enable the periodic delivery of a comprehensive, 360-degree view of usage and risk. These reports transform raw activity data into an ongoing, manageable security process by providing consistent insight into adoption trends and potential exposure.

Stage 2: Categorization 

Risk-based decision making

The challenge: Not all Gen AI tools present the same level of exposure, and security teams should consider factors such as data retention practices, compliance, and potential misuse. Without the right context, organizations risk over-restricting or allowing high-risk tools to operate unchecked.

The solution: A DLP option that offers risk-based categorization with: 

• Risk analysis and threat assessment. Once Gen AI usage is discovered through audit and visibility controls, administrators can use the gathered usage data and security analysis to categorize applications. This is a critical step where organizational policy is applied to the data.
• Sanctioned vs. unsanctioned classification. Based on this assessment, Gen AI tools can be classified as sanctioned or unsanctioned. Sanctioned tools are green-lighted for use (typically with defined controls), while unsanctioned tools are restricted.
• Policy alignment. This stage transforms usage data into security policy, directly influencing the configuration of access controls and DLP policies to ensure appropriate organizational governance.

Stage 3: Gradual adoption and controls

Where the (policy) magic happens

The challenge: Security teams need a way to enforce policy with nuance; blocking access to the riskiest applications while allowing controlled, safe use of approved apps.

The solution: Granular controls within the right DLP solution enable organizations to adopt Gen AI safely without compromising data security by:

• Blocking unsanctioned apps. High-risk, non-compliant Gen AI applications marked “Unsanctioned” can be entirely blocked to prevent access to services that pose unacceptable risk.
• Granular conditional access: Rather than relying on an all-or-nothing approach, access can be restricted based on user/group, device posture (think, BYOD), or specific features such as file uploads or large data transfers.
• Real-time data loss prevention: DLP controls inspect prompts and data payloads in real time as users interact with Gen AI tools. If sensitive information (e.g., proprietary source code, PII, financial data) is detected, the transfer can be blocked—preventing your organization’s information from ever reaching a Gen AI vendor’s servers or being used to train their models.

Look no further than Symantec DLP Cloud

What checks all these boxes and more? Symantec Data Loss Prevention Cloud delivers the complete lifecycle protection needed to identify Shadow AI and confidently secure your most sensitive data. With this robust, industry-lauded answer to DLP, teams can move from reactive guardrails to deliberate, ongoing governance by:

• Continuously monitoring Shadow AI usage
• Blocking high-risk, unsanctioned Gen AI applications
• Applying precise controls to sanctioned tools, including:
  • Blocking file uploads using DLP Cloud Protect policies
  • Inspecting prompts and payloads to detect and stop sensitive data in real time
  • Restricting access to approved Gen AI tools by user/group

Here’s what some of this actually looks like: 

Want to view Gen AI site usage by traffic? You can compile a list that spans across the organization.

Comprehensive, digestible data doesn’t stop there. Impress leadership and keep teams up to speed with a 360° report highlighting what Shadow AI looks like right now, scheduled to hit email inboxes whenever you choose.

Ready to get a grip of Gen AI? Explore how Symantec DLP Cloud takes the guesswork out of Shadow AI and turns it into a governed, manageable part of your security strategy.