68% of employees use unauthorized AI tools at work. 45% paste confidential data into public AI. Our governance framework discovers, classifies, and controls shadow AI.
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Shadow AI is any artificial intelligence tool your employees use without IT or security team knowledge. ChatGPT, Gemini, Claude, Perplexity, AI browser extensions, AI writing assistants — if it wasn't approved, it's shadow AI. And every prompt is a potential data leak.
Employees paste customer PII, financial projections, legal contracts, and source code into public AI tools to get faster answers. That data may train future models or be stored on servers outside your control.
When employees use personal accounts on external AI tools, you have no logs, no DLP triggers, and no visibility. In a breach or compliance audit, you cannot prove what data left your environment.
HIPAA, SOC 2, GDPR, and PCI DSS all have requirements around where protected data can be processed. Public AI tools are rarely on your approved vendor list — meaning every AI-assisted task may be a violation.
Malicious content embedded in documents or websites can hijack AI tools your employees use, causing them to exfiltrate data, take unauthorized actions, or produce harmful outputs — all silently.
We don't just block tools — we build a governance layer that lets your team use AI productively while keeping your data under control.
We deploy Defender for Cloud Apps to scan your network traffic and identify every AI tool in use — sanctioned or not. You'll get a full inventory: tool name, usage frequency, risk rating, and data categories exposed.
Each AI tool is classified: Approved, Conditionally Approved, or Blocked. We score on data residency, privacy policy, SOC 2 compliance, training data opt-out, and EU AI Act risk tier. You get a risk register your legal and compliance teams can sign off on.
We write your AI Acceptable Use Policy — practical, enforceable, and written in plain English. Includes approved tools list, prohibited data categories, prompt hygiene guidelines, incident reporting, and disciplinary framework. Employees actually read it because it's clear.
Purview DLP monitors for sensitive data patterns — SSNs, credit card numbers, HIPAA identifiers, proprietary code — being submitted to AI tools. We configure alert thresholds and automated block policies so violations are caught before data leaves your environment.
Entra Conditional Access blocks unapproved AI tools on corporate devices. Defender for Cloud Apps enforces session controls for conditionally approved tools — watermarking downloads, blocking paste of sensitive content, and logging every interaction for audit purposes.
We use your existing Microsoft 365 licenses as the foundation — no new vendors, no new agents, no new attack surface.
Data Loss Prevention policies detect and block sensitive data — PII, financial records, health information, trade secrets — from being submitted to AI tools via browser, app, or API.
Learn about DLP →Discovers all cloud apps in use across your organization, scores each one by risk, and enables granular session controls — block, monitor, or allow with restrictions — for any AI tool.
See AI governance →Block access to unapproved AI tools from corporate devices, require compliant device status before accessing approved AI, and enforce MFA for all AI tool sign-ins.
Conditional access details →Purpose-built AI interaction logging captures prompt content, model responses, and data categories for approved tools. Gives you the audit trail compliance frameworks require.
AI governance overview →Shadow AI refers to any AI tool or application employees use without IT's knowledge or approval — ChatGPT, Gemini, Copilot alternatives, AI writing tools, browser extensions with AI features, and more. Like shadow IT, it bypasses procurement, security review, and data governance controls.
Employees commonly paste customer records, financial data, internal strategy documents, source code, and legal contracts into public AI tools to get faster answers. That data may be used to train future models, stored on third-party servers, or exposed in a breach — all without the employee realizing the risk.
Blanket blocking backfires. Employees use personal hotspots, mobile browsers, and home networks to access the same tools. It also kills productivity and drives shadow usage underground where you have zero visibility. A governance framework — discover, classify, policy, monitor, enforce — is far more effective than a firewall rule.
We deploy Microsoft Purview DLP to detect sensitive data leaving via AI prompts, Defender for Cloud Apps (MCAS) for shadow app discovery and session controls, Entra Conditional Access to enforce approved AI tool access, and AI-specific monitoring for prompt-level data leakage detection.
Discovery and classification typically take 2-3 weeks. Policy development and stakeholder sign-off add another 1-2 weeks. Technical deployment of controls runs 2-4 weeks depending on your environment. Most organizations reach a governed state within 6-8 weeks of kickoff.
We'll run a no-cost shadow AI discovery scan and show you exactly what's in use — before it becomes a breach.