Most AI pilots in legal fail. Not because the technology isn’t capable, but because it’s asked to work without rules. Too often, teams hand over templates and expect AI to behave like a lawyer. It doesn’t work. Templates show what a “perfect” draft looks like, but they don’t explain what happens when terms deviate. Without clear rules, fallback positions, and escalation points, AI is left to guess — and lawyers don’t trust guesses.
The problem becomes obvious when comparing your own paper with third-party paper. On your own contracts, AI can enforce with surgical precision, checking clauses word-for-word. But third-party drafts never match your templates. Here, playbooks must shift from enforcing exact language to evaluating outcomes. Is the liability cap within range? Is governing law acceptable? If not, escalate.
For AI to do this reliably, rules must be clear and testable. Vague preferences and “it depends” don’t scale. That’s why frameworks like Identify → Check → Act are so valuable: they break down judgment into steps a machine can consistently follow.
None of this makes lawyers less important. It makes them central. Lawyers are the architects of playbooks, capturing strategy and risk tolerances, and the quality controllers who refine rules through testing and iteration. AI takes on the repetitive, rules-based checks, while lawyers focus on strategy, risk, and negotiation.
The bigger shift is seeing playbooks as more than efficiency tools. They’re about control. If lawyers don’t define the rules, someone else will — vendors, counterparties, or the AI itself. To make AI contract review succeed, lawyers must stop thinking of themselves only as reviewers and start acting as system designers.