As organizations deploy AI at scale, legal teams and InfoSec leaders are increasingly asked to demonstrate transparency into how AI systems are built, trained, and integrated. Two emerging disclosure artifacts, AI SBOMs (Software Bills of Materials for AI systems) and AI Model Cards, serve different but complementary purposes in managing legal, regulatory, and operational risk. A panel of cybersecurity attorneys and professionals examines how each framework supports contractual compliance, third-party risk management, IP and licensing analysis, and evolving regulatory expectations. The discussion will also explore limits on LLM usage, the role of documentation in incident response and litigation readiness, and how structured transparency artifacts can strengthen AI governance programs.