EPISODE 41 | January 09, 2026

AI Governance & Data Privacy Compliance for GTM

Expert guidance on navigating AI governance, data privacy regulations, and compliance requirements for B2B tech companies

Key Takeaways

High-risk processing triggers compliance: Healthcare, housing, employment, financial decisions, and loans are high-risk areas - if your AI touches these, expect heavy regulatory scrutiny under Colorado AI Act, EU AI Act, and California ADMT
Controller vs Processor matters: In B2B relationships, understand your role - as a service provider you're a processor with limited data use; this affects your DPA requirements and what promises you can make
Avoid claiming 'anonymization': Don't assert anonymized data - it's nearly impossible to prove and can be reidentified. Use 'deidentification' or 'aggregation' instead, which have clearer legal definitions
Trust centers reduce sales friction: Having DPAs, SOC 2 reports, and security documentation ready in a trust center dramatically speeds up enterprise sales - it's becoming table stakes for B2B SaaS
Build governance from day one: Re-engineering for privacy is costly - architect AI governance, data flows, and retention policies from the start using frameworks like NIST AI Risk Management

Jenny Lynn Sheridan and Constantine Karbaliotis, Privacy & AI Governance Experts

AI Governance, Data Privacy, GDPR, CCPA, EU AI Act, Colorado AI Act, Privacy Impact Assessment, Data Processing, Compliance Frameworks

Strategies, insights, and best practices for person-level visitor identification and AI-powered go-to-market.

GDPR

CCPA