Shadow AI Monitoring: How to Track AI Use Without Blocking It

Implementing shadow AI monitoring is essential for organizations to manage the risks associated with unauthorized AI tool usage, as banning these tools merely shifts their use to personal devices, and ignoring them allows sensitive data to be exposed to unvetted models. With the surge in generative AI traffic reported by Palo Alto Networks, primarily occurring outside formal IT oversight, monitoring provides a balanced approach to risk management while maintaining productivity. Various methods, including network and traffic monitoring, endpoint and browser monitoring, SaaS and OAuth monitoring, data-layer monitoring, and cultural surveys, each offer unique benefits and tradeoffs for capturing AI activity. Combining these strategies ensures comprehensive visibility and governance, allowing IT leaders to address specific risks effectively. Superblocks offers a platform to govern AI applications by providing audit logs and visibility, making it easier to manage shadow AI and ensure safe app development within an enterprise framework.

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