SOC 2 wasn’t written for AI. But customers still demand proof of trust. The question is: are we adapting our frameworks, or just checking boxes that no longer fit?
In this episode of Securing AI, we unpack the tension between legacy compliance frameworks and modern AI-driven products. SOC 2 remains the gold standard for SaaS trust, but when models learn, evolve, and operate autonomously, traditional control criteria start to fall short.
We explore:
- Why SOC 2’s Trust Services Criteria must be reinterpreted for AI systems
- How to map AI risks like model drift, data lineage, and API dependency to existing controls
- The danger of claiming compliance without addressing model transparency, privacy, and third-party AI providers
- What founders, CISOs, and security leaders must do to maintain credibility with enterprise buyers
This isn’t about passing an audit, it’s about proving trust in an era where AI decisions are no longer fully explainable.
Listen in if you're building, deploying, or governing AI products and want to turn compliance from a checkbox into a strategic trust advantage.
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