Artificial intelligence contract management: which parts of the job a model does well, which it does badly, and where a person still has to sign off

Updated

Artificial intelligence appears in this category in three distinct places, and they carry very different risk. Reading existing agreements to extract facts. Drafting new agreements from a prompt or a template. And answering questions across a set of contracts in ordinary language. The first is largely useful, the second needs care, and the third is only as good as the extraction underneath it. This page is about which is which, and about the one rule worth keeping whatever the tooling.

Extraction: the part that works, with one exception

Pulling parties, dates, values and clause types out of executed agreements is now reliable enough to be worth using on a backlog, and it turns a filing-cabinet problem into an afternoon. The exception is the notice period, where the wording is too varied and too often amended elsewhere for confidence. Accept extracted parties and dates, sample the clause types, and read every notice period yourself.

Drafting: useful for a first pass, dangerous as a final one

A model will produce a plausible agreement quickly, and plausible is the problem. It will omit a term nobody asked for, or include one that does not fit the deal, and neither omission announces itself. Treated as a first draft to be edited by somebody who knows the deal, it saves time. Treated as a finished document because it reads well, it is how businesses end up signing terms nobody chose.

Question answering across a set of contracts

Asking which agreements contain a change-of-control clause, or what the longest notice period in the estate is, is a genuinely useful thing to be able to do in plain language. Its accuracy is entirely the accuracy of the underlying record: if the fields are wrong, a confident wrong answer is worse than no answer, because nobody checks a fluent one.

The rule worth keeping

A model may fill a field; a person confirms anything with a date or a number attached before it becomes the record. That single rule keeps the speed and removes almost all of the risk, because the failures in this category are quiet rather than loud. TermsBird keeps the record and expects the person, which is why the fields it holds are short enough to check.

Questions people ask about artificial intelligence contract management

Can AI manage contracts?

It can extract facts, draft first passes and answer questions across a set. It cannot decide what to sign or be relied on for a notice period without checking.

Is AI contract drafting safe?

As a first draft edited by somebody who knows the deal, yes. As a finished agreement because it reads well, no: the failures are omissions that do not announce themselves.

What should a person always check?

Anything with a date or a number attached, especially notice periods. Those are the fields where an error costs money and where extraction is weakest.

Does AI replace a contract record?

No. It can populate one faster. The record is still what everything downstream reads, and it still has to be right.

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