Governance

MSSPs are under pressure to deliver AI relevance as generative AI adoption is accelerating faster than traditional security controls can catch up. Enterprises are embracing tools like ChatGPT, Copilot, and Gemini across departments, often without oversight — creating fresh risks, compliance obligations, and uncertainty. For MSSPs, this represents both a challenge and an opportunity: a chance to provide clarity, guardrails, and governance that make GenAI security a top customer priority.

Your colleagues are using GenAI right now—but probably not in the way your IT team intended. From data leaks to app overload, organizations are learning that enabling GenAI isn’t just about buying a license—it’s about rethinking policy, trust, and productivity. Here’s what we’ve learned.

Before diving into the how of security and governance tooling, you must first understand the what of enforcement. Evaluating tools based solely on their technical features and implementation details won’t deliver meaningful results. Success in GenAI governance starts with clearly defining what needs to be enforced—only then can you determine how to do it effectively.

Best Practices for Securing Public GenAI Apps and LLM Apps in the Enterprise