Anne represents domestic and multinational corporations in complex commercial litigation and trade secret actions in state and federal courts in California and nationally. She focuses her practice on trade secret misappropriation claims and business tort disputes including unfair competition claims and breach of contract. She also advises clients on litigation avoidance and best practices relating to contract provisions and trade secret protection. Anne is a member of the Firm's North America Trade Secrets Practice Group.

Bradford Newman is a litigation partner resident in Baker McKenzie's Palo Alto Office and Chair of the North America Trade Secrets Practice. According to Chambers USA, Brad is a "recognized authority on trade secrets cases" who "is valued for his tenacious, intelligent and thoughtful approach to trade secrets matters." Bradford regularly serves as lead trial counsel in cases with potential eight and nine-figure liability and has successfully litigated (both prosecuting and defending) a broad spectrum of trade secrets cases in state and federal courts throughout the country. He routinely advises and represents the world's leading technology, banking, professional service, manufacturing and commerce companies in connection with their most significant data protection and trade secret matters. Bradford is the author of Protecting Intellectual Property in the Age of Employee Mobility: Forms and Analysis, a comprehensive treatise published by ALM that offers authoritative guidance on legal risks and practical steps companies can take to protect their IP and remedy IP theft.

Bradford specializes in matters related to trade secrets and Artificial Intelligence. He is the Chair of the AI Subcommittee of the ABA. Recognized by the Daily Journal in 2019 as one of the Top 20 AI attorneys in California, Bradford has been instrumental in proposing federal AI workplace and IP legislation that in 2018 was turned into a United States House of Representatives Discussion Draft bill. He has also developed AI oversight and corporate governance best practices designed to ensure algorithmic fairness.