Governance and guardrails for employee usage
CISO Guide: Best Practices for Securing Public GenAI apps and LLMs in the Enterprise
New use cases and specialized apps every day
Use cases expand beyond agreed scope
Employee training is quickly outdated
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Data leak through model training
Hallucinatory content entering businesses
Inability to verify staff compliance with policies
Unable to show how employees use GenAI
Data protection cannot guard prompts and responses
Minimal guidance to users about safe usage
By looking at the real usage, data flows and risk exposures
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By automatically gating access based on data protection terms and risk profiles
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By enforcing policies on data usage and generated content based on job role needs
By adding a safety net that removes accidental data leaks
Best Practices for Securing Public GenAI Apps and LLM Apps in the Enterprise
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It is very positive that the big GenAI vendors, like OpenAI, Microsoft and others, have been granting more transparency into how they treat the content they collect from their end users. It’s only reasonable that you know where your prompt may end up. Will it be used to train the model, or will it even show up in an AI generated response to somebody else?
