Read
2 minute read
August 3, 2026
2 minute read
Contract review has quickly become one of the most common business uses for AI, including summarizing terms, identifying potential issues, and even drafting revisions.
However, you still need to verify the results. I recently had a client ask me only to review a specific provision. They had used AI to conduct their initial review and were comfortable with the other provisions. When I reviewed, the provision itself appeared reasonable. However, while skimming potentially related provisions that could be impacted, I found a clause buried in the Miscellaneous section that allowed the other party to unilaterally modify the agreement with notice.
Suddenly, the provision my client wanted reviewed didn't even matter. If one party can change the terms after the agreement is signed, any redlines and negotiations now could be unilaterally wiped away.
Their AI review missed this. Before relying on AI-generated results, make sure to verify the results. Consider the following:
1. Think About What's Missing
Most AI tools do a good job identifying provisions that are included in an agreement. The harder task is recognizing provisions that are missing. Often times AI doesn't have the full background and the underlying relationship. When reviewing AI-generated output, ask yourself: "What should be here that isn't?" Spotting the absence of something requires contextual knowledge about the deal, the relationship, the industry, and the regulatory environment. A reviewer who doesn't know that a particular transaction triggers ITAR compliance obligations, for example, won't flag the missing export control provisions. AI tools still struggle with bespoke gaps that depend on facts outside the four corners of the document.
2. A Summary Is Not a Risk Assessment
AI is very good at summarizing contract language. That doesn’t mean it can fully assess business risk. For example, an AI tool may correctly state: "The supplier's liability is capped at the fees paid during the preceding twelve months." That summary may be accurate. The harder question is whether that liability cap adequately protects your business. A liability cap of trailing twelve-month fees might be perfectly acceptable for a low-value SaaS subscription but inadequate for a mission-critical infrastructure provider. The question is not simply whether AI understands the clause. The question is whether the clause makes sense for your business.
3. Verify
AI makes mistakes. We have all used it, questioned an answer, and AI’s response will be "You're right, I made a mistake." This is not very helpful and doesn't inspire confidence. Additionally, the tendency of AI models to agree with corrections — even incorrect ones — is a known limitation. AI-generated outputs are also only as good as the initial prompt; a generic instruction to "review this contract" will produce shallower results than a targeted request to identify specific risk areas. Verify the outputs. Spot-check key conclusions against the contract language, and don't assume that silence on an issue means the issue isn't there.
AI is changing the way contracts are reviewed, and for many organizations it is already becoming an indispensable tool. Used properly, it can improve efficiency, identify issues, and allow legal and business teams to focus on higher-value analysis.
But AI should be viewed as a starting point, not the final answer.
