To ensure compliance with regulations and security standards in AI applications, organizations must focus on access control and data processing methods. Jack Berkowitz, chief data officer at Securiti, emphasizes the importance of identifying who can access sensitive information and how it is managed within generative AI environments. He warns that relying solely on static security measures will be inadequate as AI evolves. To mitigate risks from rogue AI agents, robust guardrails are essential. Joanne Friedman, CEO of ReilAI, adds that while many enterprises have established sound security practices—like secure SDLC, encryption, role-based access control, and compliance with regulations such as GDPR, HIPAA, and CCPA—these measures fall short in the dynamic landscape of AI. Organizations must adapt and enhance governance frameworks to address the rapidly changing nature of data and AI behavior, ensuring robust security and compliance.
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