AI Regulation and What Every Tech Company Should Know

Shannon Yavorsky, who co-leads Orrick’s AI practice, cyber/privacy, and data innovation group, joins Kevin Ball of Mento to explain the shifting AI regulatory landscape. She frames AI law as overlapping risk circles—privacy, cybersecurity, employment, IP, and consumer protection—and shows CIOs how to build governance around transparency, safety, and accountability rather than chase every new statute.

Key points

• U.S. AI governance is a patchwork of 150+ state AI laws, plus privacy, cybersecurity, employment, IP, and consumer-protection rules.
• Start with your product, use case, data type, and geography; don’t try to master every law at once.
• Core governance principles: transparency, fairness, safety, and accountability with documented decision-making.
• Shadow AI and recorded meetings create litigation and discovery risk; enterprise controls reduce exposure.
• High-risk uses like lending and health data need stronger controls than low-risk manufacturing use cases.
• Orrick created an AI Law Tracker because 1,500 AI bills were proposed at state level last year.