A clear-eyed look at where AI drafting saves real time and where it still needs a careful human edit.
Key takeaways
Given a firm's actual precedent library, AI can assemble a structurally sound first draft, correct clause ordering, standard boilerplate, consistent defined terms, far faster than a junior working from scratch. That's a real, measurable time saving.
It's particularly strong at producing a starting point for routine agreements, NDAs, standard service agreements, where the variation between engagements is limited.
AI drafting is weakest on the parts of a contract that reflect genuine negotiation, specific liability caps agreed in a call, an unusual carve-out a client insisted on. These need a lawyer's judgment and can't be reliably inferred from a template.
It can also produce plausible-sounding language that doesn't actually match the jurisdiction's requirements if it isn't grounded in your firm's own vetted precedents.
Firms that get poor results are often feeding the tool generic internet templates instead of their own vetted precedents. The output is only as good as what it's drawing from, and a firm's own precedent library, refined over years, is a far better source.
Investing a few days upfront organising and tagging your best precedents pays off in every draft that follows.
Every AI-drafted contract needs a full review from a qualified professional before it goes to a client, checking both the substance and the specific negotiated points that no template could have anticipated.
Treat the AI draft as saving the associate an afternoon of assembly work, not as saving the partner's review time. Both steps still need to happen.
A 30-minute call is enough to tell you whether AI pays for itself here.
