Shadow AI - create a safe, controlled AI adoption journey
Four ways organisation's can use Microsoft Purview to protect against Shadow AI.
Introduction:
The rise of generative AI tools like Copilot, ChatGPT and Gemini, is transforming the organisations workplace and productivity — but it’s also fueling the growth of Shadow AI, where employees use AI services outside of official IT oversight, boundaries or policies.
Shadow AI can lead to data leaks, compliance violations, and increased risk. Microsoft Purview offers powerful capabilities to help discover, monitor, and control shadow AI usage.
With that said, here are 4 ways you consider Microsoft Purview to help with your Shadow AI risks today!
1. Discover and Classify Sensitive Data Accessed by AI Tools
Shadow AI risks start with sensitive data usage and exposure at the core. With Microsoft Purview Data Map and Classification, you can scan your environment, particularly cloud and on-premises repositories to identify sensitive data types that employees might upload, use or input into AI tool prompts. Providing this visibility allows for the automated application of sensitivity labels like "Confidential" or "Highly Confidential" to tag and protect data to block the use of this content, ensuring AI tools can’t accidentally process unclassified sensitive information.
2. Enforce Data Loss Prevention (DLP) for AI-Generated or Consumed Data
Shadow AI can often involves employees copying sensitive data into AI prompts or uploading documents to AI SaaS apps. Either way, Microsoft Purview DLP policies can warn or block users when they attempt to share protected data with unauthorized services. This is all dependant on the policies defined by IT or policies enforced. Customised policies with keywords related to AI (e.g., “GPT”, “AI tool”) or to block traffic or to monitor prompts and responses known AI tool URLs to stop data exfiltration in real-time — even on endpoints and browsers plug-ins.
3. Monitor Data Activities with Audit and Insider Risk Management
It is important to always monitor and know ‘good behavior’ for your users. You can use Microsoft Purview Audit to capture detailed logs of how data is accessed and used across your organisation. Audit events can help you spot potential shadow AI activities, such as suspicious data downloads or uploads to AI services. Combine this with Insider Risk Management to set policies that detect abnormal user behavior, alerting you when employees access or share sensitive data in ways that suggest shadow AI usage. Over time, you can continue to monitor activities and mature your policies to match.
4. Implement Data Security Posture Management (DSPM) for Continuous Assessment and Optimisation
As AI tools evolve, so do shadow AI risks. Microsoft Purview DSPM gives you a continuous, holistic view of your data security posture. DSPM identifies exposure points — like unsecured repositories employees could feed into AI — and recommends remediation. Coupled with sensitivity labels, DSPM helps ensure your data governance strategy stays adaptive and aligned with new AI risks.
Conclusion
Shadow AI doesn’t have to be a hidden threat. By working with the right tools and experienced partners you can combine the best of discovery, monitoring, DLP enforcement, and continuous assessment through Microsoft Purview, and your organisation can regain visibility and control, enabling employees to harness AI responsibly without sacrificing security or compliance.
