SHADOW AI

Your Employees Are Using AI.
You Just Don't Know It Yet.

Shadow AI — unauthorized use of AI tools by employees — is the fastest-growing blind spot in enterprise security. Your workforce is pasting sensitive data into ChatGPT, Claude, and dozens of other tools you've never approved and can't monitor.

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78%

of employees use unapproved AI tools at work

WalkMe/SAP 2025
46%

of organizations have had data leaks via GenAI

Cisco 2025
Only 23%

of organizations require staff training on approved AI usage

Gartner via UpGuard

What Is Shadow AI?

Shadow AI is the use of artificial intelligence tools by employees without the knowledge, approval, or oversight of IT and security teams. It's the AI equivalent of shadow IT — but with far higher stakes because every interaction involves sending data to an external provider.

It happens because AI tools are incredibly easy to access. An employee can open ChatGPT in a browser tab, paste a customer spreadsheet, and get analysis in seconds. No procurement process, no security review, no data processing agreement. They're not being malicious — they're being productive. But from a security and compliance perspective, it's uncontrolled data exfiltration.

Common examples include developers pasting proprietary source code into AI coding assistants, HR teams running employee data through ChatGPT for analysis, legal teams uploading contracts for summarization, and sales teams feeding customer data into AI tools to draft proposals.

The Risks of Shadow AI

Every unapproved AI interaction is a potential data leak, compliance violation, or IP exposure. These risks compound as adoption grows.

Data Leakage

Critical

Employees paste sensitive customer data, credentials, and internal documents into AI tools your security team doesn't monitor.

Compliance Violations

Critical

Unmonitored AI usage makes it impossible to demonstrate compliance with GDPR, HIPAA, the EU AI Act, or industry regulations.

No Vendor Oversight

High

When employees sign up for AI tools individually, there are no data processing agreements, no security reviews, and no contractual protections.

Intellectual Property Exposure

Critical

Proprietary source code, product roadmaps, and trade secrets are shared with AI providers who may use that data for model training.

Cost Sprawl

Medium

Dozens of individual AI subscriptions across departments. No centralized billing, no volume discounts, no budget visibility.

Inconsistent Policies

High

Each team sets its own rules for AI use. Engineering may be cautious while marketing shares everything. No enforcement, no consistency.

Why Blocking AI Doesn't Work

Organizations that try to ban AI tools find that employees use them anyway — 78% already do. The question isn't whether your employees use AI. It's whether you have any visibility into how they use it.

Ban AI tools entirely

Not practical

Pros

  • Eliminates data risk on paper

Cons

  • Employees use them anyway (78% already do)
  • Competitive disadvantage
  • Talent retention issues

Approved tools only

Necessary but insufficient

Pros

  • Limits vendor sprawl
  • Enables DPAs

Cons

  • Doesn't prevent data in prompts
  • No enforcement mechanism
  • Shadow AI persists alongside approved tools

Network-level monitoring

Incomplete

Pros

  • Visibility into AI domains accessed

Cons

  • Can't inspect encrypted prompt content
  • No PII detection
  • Can only block or allow — no scrubbing

AI security gateway

Comprehensive

Pros

  • Inspects and scrubs prompt content
  • Works across all AI tools
  • Complete audit trail
  • Policy enforcement per role and data type

Cons

  • Requires deployment

How Tenlines Detects Shadow AI

Tenlines operates as an AI security gateway between your workforce and every AI provider. It doesn't block AI — it governs it.

Traffic Interception

Sits between employees and all AI providers. Every prompt and response is captured, whether the tool is approved or not.

PII Detection

Regex patterns and ML-based NER identify names, emails, SSNs, credit cards, and credentials before they reach AI providers.

Code Protection

Semantic similarity matching detects when proprietary source code is being shared with AI, even if modified or paraphrased.

Policy Enforcement

Role-based rules define what data each team can share. Engineering, legal, and marketing can have different policies.

Real-Time Audit Log

Every AI interaction is logged in JSONL format. Who sent what, when, to which provider, and what was scrubbed.

Shadow AI Discovery

Identifies which AI services employees are actually using — approved or not — giving security teams full visibility.

From Shadow AI to Governed AI

The goal isn't to stop employees from using AI. It's to make AI usage visible, safe, and compliant. Here's what changes with Tenlines in place.

Before Tenlines

  • No visibility into AI tool usage
  • PII and secrets sent to AI providers
  • No audit trail for AI interactions
  • Policies vary by team with no enforcement
  • Compliance gaps for GDPR, HIPAA, EU AI Act
  • Proprietary code shared freely with AI

After Tenlines

  • Full inventory of every AI tool in use
  • Sensitive data scrubbed before it leaves
  • Complete JSONL logs of every prompt and response
  • Centralized, role-based policies enforced automatically
  • Auditor-ready evidence of AI data governance
  • Semantic code matching blocks IP from leaving

Take Control of Shadow AI

Shadow AI isn't going away. Your employees will continue using AI tools whether you approve them or not. The choice is between blind spots and visibility. Tenlines gives you the visibility — without slowing anyone down.