Over the next several weeks, I am focusing on one of the most underappreciated legal risks of the AI era: discoverability. Each post will examine a different AI tool and how the records it generates can become a serious liability in litigation.
I will start with a case that should be required reading for anyone who has ever typed a sensitive question that might have legal implications into a generative AI system.
If your team is writing software without generative AI, your competitors may soon be outpacing you. If your team is using it without proper controls, you may be building a codebase you don’t actually own.
That second risk is less obvious, and it tends to surface late. A company builds a product using AI coding tools, ships it, and begins attracting acquisition interest. During diligence, buyer’s counsel asks about a portion of the codebase.
Every day, thousands of business meetings are recorded by AI notetaking apps. Most participants click “Join,” enter the meeting, and only then see the platform’s default recording notice. That casual click may not be enough to make the recording legal — and for businesses operating across multiple U.S. states, the exposure is real.
B2B rebate programs consistently outperform traditional discounts in loyalty, margin protection, and strategic insight. Discounts may close deals quickly, but they often erode value and provide little insight into partner engagement.
Read More
The California Supreme Court recently clarified joint and several liability in multi-party contracts, finding jointly and severally liable parties may be sued in separate lawsuits. Read Ken Van Vleck’s article published by the American Bar Association, Section of Litigation here.