To ensure accuracy in its legal AI, LexisNexis unexpectedly hired a large number of lawyers, not just data scientists. These legal experts are crucial for reviewing AI output, identifying errors, and training the models, highlighting the essential role of human domain expertise in specialized AI.

The most potent productivity gains from AI aren't just for junior staff. Seasoned professionals who combine deep domain expertise with adaptability are using AI to rapidly learn adjacent skills like design or marketing. This allows them to "collapse the skill stack" and single-handedly perform tasks that previously required multiple people.

While AI-native, new graduates often lack the business experience and strategic context to effectively manage AI tools. Companies will instead prioritize senior leaders with high AI literacy who can achieve massive productivity gains, creating a challenging job market for recent graduates and a leaner organizational structure.

AI tools are taking over foundational research and drafting, tasks traditionally done by junior associates. This automation disrupts the legal profession's apprenticeship model, raising questions about how future senior lawyers will gain essential hands-on experience and skills.

While many believe AI will primarily help average performers become great, LinkedIn's experience shows the opposite. Their top talent were the first and most effective adopters of new AI tools, using them to become even more productive. This suggests AI may amplify existing talent disparities.

The traditional law firm model relies on a large base of junior associates for grunt work. As AI automates these tasks, the need for a large entry-level class shrinks, while mid-career lawyers who can effectively leverage AI become more valuable, morphing the firm's structure into a diamond shape.

If AI were perfect, it would simply replace tasks. Because it is imperfect and requires nuanced interaction, it creates demand for skilled professionals who can prompt, verify, and creatively apply it. This turns AI's limitations into a tool that requires and rewards human proficiency.

Measuring AI's value by hours saved is misleading for law firms, as it can imply lower revenue. The true ROI comes from what lawyers do with that saved time: pursuing more complex strategies, conducting deeper analysis, and spending more time with clients—high-value work previously constrained by time.

A top-tier lawyer’s value mirrors that of a distinguished engineer: it's not just their network, but their ability to architect complex transactions. They can foresee subtle failure modes and understand the entire system's structure, a skill derived from experience with non-public processes and data—the valuable 'reasoning traces' AI models lack.