A law firm asked me to build an AI that reviews contracts.

The first prototype highlighted 94% of risky clauses correctly.

The lawyers' response: "What about the 6% it missed?"

Fair point. In legal work, a missed clause can cost millions. The standard isn't "usually right." It's "never misses anything important."

So we redesigned the system: instead of making binary decisions, the AI flags potential issues with confidence scores and highlights the relevant text. Lawyers still make every decision. But instead of reading a 200-page contract line by line, they review 30 flagged sections.

Time saved: about 70% per contract review. No clauses missed, because the human still reads everything the AI is uncertain about.

This is the pattern that works for high-stakes AI applications. Don't try to replace expert judgment. Reduce the workload so experts can focus their judgment where it matters.

The legal AI market is growing fast because law firms bill by the hour, and anything that reduces hours on low-value tasks frees up hours for high-value work.

If you understand both NLP and legal document structure, you're positioned for a market that's desperate for builders.