How to Build an AI Compliance Program

In this episode of KLF Deep Dive, Darshan Kulkarni explores the growing urgency for in-house counsel to develop AI compliance programs as artificial intelligence becomes embedded in drug discovery, clinical decision-making, patient engagement, and beyond.

Darshan emphasizes that AI can create significant legal risk—even without breaking the law—if companies fail to address issues of transparency, validation, privacy, and governance. As regulators like the FDA and FTC tighten their expectations, companies must proactively implement structured, cross-functional AI compliance programs.

Key Topics Covered:

• AI System Mapping
   Start by identifying all AI systems—internally developed or third-party. Understand who owns them, what data they use, and how they function. Create a living inventory that evolves with your organization.
• Validation & Explainability
   Ensure that your models are transparent, repeatable, and auditable. Document how decisions are made and build mechanisms to detect deviations. Explainability is no longer optional—regulators and litigators expect it.
• Privacy & Governance
   Align your AI systems with HIPAA, GDPR, and state privacy laws. Update privacy notices to disclose AI use and profiling. Legal and privacy teams must collaborate closely with AI developers.
• Monitoring & Decommissioning
   All systems fail or become outdated. Put in place processes to log errors, recalibrate models, and decommission AI tools without disrupting patient care.
• Contracting & Vendor Management
   Negotiate contracts that clearly define data rights, IP ownership, use limitations, and audit rights. Tie these terms back to your insurance coverage and risk allocation.
• Risk Assessment
   Use risk registers to evaluate AI systems for potential misuse, bias, or patient harm. Prioritize mitigation efforts and build policies based on real-world use, not theoretical frameworks.
•  Culture & Training
   AI compliance isn’t a document—it’s a system. Cross-functional teams (legal, medical, IT, marketing) must be trained regularly. Appoint internal champions to maintain risk maps and trigger policy updates.

Conclusion:

If your organization doesn’t know who governs each AI system—or if your contracts don’t cover AI-specific risks—you’re already behind. Now is the time to build an adaptive, defensible AI compliance program that scales with your innovation.

Kulkarni Law Firm helps pharma and health tech companies translate AI risk into operational clarity. Subscribe to KLF Deep Dive for more weekly insights at the intersection of legal risk and life science innovation.

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