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"The Compliance Risks of Generative AI: A CISO's Playbook"

Mapping Exposure, Establishing Benchmarks, and Building Defensible AI Governance

Generative AI is entering the enterprise faster than compliance frameworks can adapt. Employees are using copilots built into everyday software, experimenting with AI-native tools, and routing sensitive data through systems that have never been vetted. Each of these actions introduces new compliance risks, from HIPAA and SOC 2 violations, to data residency conflicts and unauthorized model training.

This paper defines the expanding AI domain landscape and explains how two categories of tools — embedded AI features inside established SaaS platforms and standalone AI-native providers — create distinct regulatory exposures. It explores how these risks manifest through data flows, shadow use, and third-party dependencies, and how security leaders can regain visibility and control. 

The playbook provides a framework for CISOs to conduct risk audits, evaluate providers, and demonstrate defensibility to boards and regulators as AI adoption accelerates.

Readers will learn:

1. How embedded and AI-native tools create hidden compliance gaps.
2. The key exposure areas: HIPAA and SOC 2 alignment, data residency, free-tier usage, and consent.
3. Why shadow AI represents a growing AI governance failure for enterprises.
4. How to structure due diligence across providers and track data handling in real time.
5. How to turn risk audits into a repeatable compliance framework that satisfies leadership and auditors.

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