Entrepreneurship. It has such a romantic ring, doesn’t it? When we hear the word, we think of incredibly successful people who must lead a charmed life. But the truth of the matter is often far from that. Just ask Melissa Rogozinski whose recent book, Becoming Phoenix, tells a much different story.
Agentic AI introduces risks that are novel and complex, but the most effective response is a familiar one. Zero Trust answers the problem of when an AI agent misfires on its own by constraining what an agent can do rather than betting on how it will behave.
California is betting that it can accelerate AI adoption by acting as a demanding, trusted buyer, and that the governance evidence it extracts through procurement can become infrastructure the rest of the market reuses.
Why advanced AI will change legal practice without making lawyers obsolete.The future value of lawyers will come less from generating first drafts and more from knowing how to choose, feed, test and deploy professional systems in a way that serves the client’s strategy.
Companies are no longer judging leaders on what they have already done. They are judging them on whether they can lead what is coming next. And what is coming next demands exactly the quality that defined the Oregon Trail generation: the ability to navigate genuine transformation, not just manage through disruption.
Before asking whether AI use is permissible, defensible or reliable, practitioners have to identify what function the system is supporting in the legal workflow. Treating all legal AI as a single category obscures the actual source of professional risk: not the existence of AI itself but the role the system plays in the provision of legal services.
The children’s privacy risk model is changing in the United States. Historically, many businesses could credibly say they did not know whether children or teens were using their apps and services. Now, that defense is becoming harder to sustain, bringing with it a wave of potential compliance obligations.
Firms are investing heavily in AI-powered business development tools and simultaneously ignoring the data foundation those tools require to function. You cannot prompt your way out of bad data. Garbage-in, garbage-out. On a galactic scale.
Part 1 of this article outlined five barriers blocking legal AI adoption — drawn from more than a hundred conversations with legal leaders. But identifying barriers isn’t the same as overcoming them. Some teams have broken through. What separates them from the rest?
Part Two of a Multipart Article. Part One is here.Litigation involving AI rarely turns on abstract questions about the technology itself. Instead, disputes typically focus on how AI was deployed, what contractual promises govern its use and how responsibility for AI-driven outcomes is allocated between providers and customers.
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