Contract review workflows in the AI era
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"Contract review" means slightly different things to different people. One person thinks of it as finding dangerous clauses. Another thinks of it as drafting a revision to send the counterparty. Business teams call it a "legal check," while legal itself splits the work into review, redlining, drafting comments and organizing risk without always distinguishing between them. This vagueness contributes to slow review: when nobody has settled what "review" actually covers, legal tends to read too broadly every time, and the business team has no clear sense of what it is waiting for. This article works through how to run contract review in practice, and where AI can help versus where a person still needs to decide.
Review is more than checking clauses
Reviewing a contract means confirming its content and judging whether the terms are acceptable, but in practice that covers more than legal validity alone. It includes identifying the contract type, confirming the company's own position, understanding the deal's background, reviewing the main text, checking any appendix, specification sheet, SOW or quote, assessing the risk in key clauses, drafting a revision, writing an internal comment, writing a comment for the counterparty, and working out a negotiation stance. A clause that looks unremarkable on its face can carry very different risk depending on the deal behind it. A liability cap set at one month's fee might be fine for a low-cost SaaS subscription and clearly too low for a service agreement handling large volumes of personal data on core systems. Review only works once the clause is read together with the deal it actually governs.
Start with contract type and the company's position
Rather than starting at clause one, it helps to confirm the contract type and the company's own position first. The contract type tells you which clauses deserve the closest attention, and the company's position tells you which of those clauses favor the company and which do not. In an NDA, whether the company is disclosing or receiving information changes how the scope of confidentiality and permitted use should read. In a service agreement, whether the company is the client or the vendor changes how deliverables, inspection and IP ownership should read. Skipping this step at the outset tends to produce generic comments.
Match review depth to the size of the risk
Not every contract needs the same depth of review. Legal teams have limited time and staff, and treating a small, routine contract the same as a strategically important one leaves too little time for what actually matters. Depth can reasonably scale with the contract amount, term, ease of termination, whether a substitute is available, whether personal or confidential information is involved, how important the IP is, the potential impact of a loss, the counterparty's creditworthiness, past dealings and any applicable regulation. A single-use engagement worth a few hundred dollars and a multi-year deal worth millions should not get the same treatment even under the same contract template, and this prioritization is a judgment call for a person, not something to hand to AI wholesale.
Keep internal and counterparty-facing comments separate
Separating who a comment is for matters as much as spotting the risk itself. An internal comment can be direct about how severe a risk is, where a business decision is needed, and what to watch for if the company accepts it. A comment sent to the counterparty needs language that keeps the negotiation moving. The same point about a personal-data-heavy contract might read internally as "this liability cap is too low given the data-leak exposure and should be accepted only after careful thought," while the version sent to the counterparty reads more like "given that this work involves personal data, could the liability cap exclude damages arising from a data leak." The purpose of the wording differs even though the underlying issue is the same, and review quality depends on how well a risk is communicated, not only on whether it was found.
What AI can take on, and what still needs a person
Generative AI can meaningfully speed up parts of contract review: summarizing the contract, extracting clauses, running a first pass against a checklist by contract type, and drafting a first version of a comment or a revision. What still needs a person includes judging against the company's actual risk tolerance, working out which business terms are non-negotiable, calibrating how firmly to push given the relative negotiating strength, resolving points where the legal interpretation is genuinely unsettled, checking consistency with past deals, and the final call on whether to accept something. AI's output tends to work best as groundwork rather than as a substitute for the reader. Sent to a counterparty as is, it can be either too aggressive or too vague for the actual negotiation.
A workable review sequence, and common gaps
In practice, review tends to run through confirming the intake information, the contract type and the company's position, reading the main text and any appendices, focusing closely on the highest-risk clauses, separating out points that need an internal decision, drafting a revision and both sets of comments, confirming negotiation direction with the business team, and checking the revised version once it comes back. Having this sequence in place makes review noticeably more consistent than leaving it to be improvised case by case, where the depth and tone of comments tend to vary a great deal by reviewer.
A common gap is spending most of the attention on legally significant clauses while treating operational details, such as a notice contact or how inspection results get communicated, as an afterthought, even though those details can matter a great deal once an actual problem arises. Another is reading only the main text and skipping the appendix or SOW, where a heavy performance guarantee or a narrower scope of work often actually sits. Building a lightweight legal playbook by contract type, even just a note on which clauses to check and revise by default for NDAs, service agreements or SaaS terms, tends to be the fastest way to make review both quicker and more consistent, whether or not AI is involved.
LegalAgent supports the design of this review flow as well as the day-to-day work of running it.