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.

After a document is drafted, lawyers ask an AI tool to review it for missed points or alternative angles. The tool acts like an impartial third party with vast analytical recall, offering suggestions that refine and improve the final work product at a minimal cost.

In fields like law and consulting, AI will automate the generation of work products (e.g., contract reviews). This commoditization will shift value upstream to uniquely human skills like providing strategic advice and experienced judgment based on the AI's output.

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.

Within the last year, legal AI tools have evolved from unimpressive novelties to systems capable of performing tasks like due diligence—worth hundreds of thousands of dollars—in minutes. This dramatic capability leap signals that the legal industry's business model faces imminent disruption as clients demand the efficiency gains.

Instead of pursuing full automation, a powerful use case for internal agents is augmenting workflows. For example, a 'legal review' agent can screen marketing copy, approve standard material, and flag ambiguous content for human lawyers, accelerating the process without removing necessary oversight.

The most powerful current use case for enterprise AI involves the system acting as an intelligent assistant. It synthesizes complex information and suggests actions, but a human remains in the loop to validate the final plan and carry out the action, combining AI speed with human judgment.

While AI streamlines tedious tasks, its more profound impact is acting as a 'co-pilot' for lawyers. It helps them brainstorm, test theories, and think through complex problems, leading to higher-quality work product—a capability previous technologies lacked.

AI's value in a compliance platform isn't in answering binary audit questions (e.g., "is X encrypted?"). Instead, it should automate the messy, non-deterministic work around them, like finding compliance obligations hidden in legal contracts, a task previously impossible to do at scale.