In 2026, many companies are using AI to identify opportunities, model risks, summarize diligence, compare precedents, stress-test assumptions, and prepare decision memos in days rather than weeks. But if the final step before action is “send it to outside counsel and wait,” then some of the benefits of speed that they have achieved through their use of AI may be lost.
Until recently, many clients’ processes moved at roughly the same pace as their outside counsel. A business team developed an idea, the in-house legal team gathered facts, the company consulted outside counsel, and the decision moved forward when the pieces were ready. In that environment, a detailed legal memo from a law firm in two weeks could be excellent service, especially if the question was complicated, the risks were meaningful, and the answer required careful judgment.
But AI is accelerating the pace of business decision-making. For clients that are using AI effectively, the front end of many processes is getting much faster. A potential acquisition target can be screened more quickly. A regulatory question can be framed more precisely. A contract portfolio can be searched and summarized in hours. A product launch can be evaluated against prior risk assessments, market data, and internal policies before the first meeting is held. That speed is not just a convenience. In some cases, it is a significant strategic advantage, but that advantage can disappear if the outside legal advice arrives too late.
Suppose Client A needs a legal question answered before pursuing a business opportunity. Law Firm 1 can provide a comprehensive legal analysis in two weeks for $50,000, with every relevant legal issue researched, checked, and caveated. Law Firm 2, using AI-assisted workflows and experienced lawyer review, can provide advice that is sufficiently reliable for the decision at hand—a summary of the key legal considerations and practical risks, though less exhaustive in its treatment of every issue— in one week for $30,000. If the opportunity will still be available in two weeks, and the details of all the legal issues are important, the client may rationally choose Law Firm 1. But if the difference between one week and two weeks means the opportunity is lost, repriced, or materially less valuable, the comparison changes. The comprehensive legal answer may be better in the abstract, but the faster, reliably scoped answer may be more useful in the real world, leaving aside any cost savings.
That does not mean clients will stop caring about quality. It means that, for some categories of work, quality will operate more like a threshold than a sliding scale. Once the answer is sufficiently reliable for the decision at hand, speed may become the dominant variable. For those matters, “good enough by Friday” can beat “excellent next month.”
This is not a comfortable point for many lawyers. We are taught to find the issue that others missed, add the caveat that protects against overstatement, and keep refining until the analysis is as strong as we can make it. Those instincts remain indispensable. They are why clients come to sophisticated counsel for novel, sensitive, high-stakes, or bet-the-company matters. No serious client wants a rushed answer on a question that requires deep factual investigation, legal nuance, board-level judgment, or strategic calibration.
But not all legal work requires that level of interrogation. Some advice can reasonably be rough because it is only being used to decide whether to proceed to the next stage, not to make an irreversible final decision. Some projects require a risk ranking, an escalation recommendation, or a preliminary view that is clearly labeled with assumptions and limitations.
AI adoption can change a client’s internal baseline for how long outside legal advice can take. If an in-house team can use AI to prepare a first draft of a risk assessment in a day, it will be harder to accept that outside counsel needs three weeks to review it. If the business team is using AI to compare scenarios, prepare summaries, and identify open questions, then outside counsel’s advice may be expected to fit into that accelerated workflow. As clients become more sophisticated in their own AI use, they may become less patient with law firms that treat every question as though it must be answered comprehensively through a bespoke, manual process, and may start asking their firms to provide reliable advice in time for it to matter. As a result, at the outset of any project, law firms will increasingly need, as a matter of course, to confirm any hard deadlines, as well as the optimal format and detail needed for the advice to be delivered.
None of this changes the professional obligations that attach to legal advice. Fast advice must still be verified advice, and AI-accelerated workflows raise obvious questions about accuracy and quality control. But those risks can be managed the way lawyers have always managed advice: by being explicit about what was reviewed and what was not, clearly labeling assumptions and limitations, confirming the scope of the engagement in writing, and ensuring that experienced lawyers carefully review and verify AI-assisted output before it goes to the client. The result is not less rigor; it’s rigor that is proportionate to the nature and timeline of the decision being made.
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The authors would like to thank Debevoise Summer Associate Christopher Cokinos for his contribution to this blog post.
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The cover art used in this blog post was generated by ChatGPT.
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