That grace period is out the window for artificial intelligence. Firms may still be debating when and how aggressively to adopt it, but their clients are no longer waiting. AI is no longer simply a technology decision. It is becoming a necessity for client relationships.
Clients Are Already Grading Firms on AI
Individual use of generative AI among legal professionals is rapidly increasing. Yet firmwide training, implementation and governance have not kept pace. That gap can create inconsistent practices around confidentiality, accuracy and client data.
At the same time, clients are expecting the opposite. They want a coherent answer about how their outside counsel is using AI and what value they are getting from it.
Thomson Reuters' 2026 Future of Professionals Report found that 78% of corporate clients consider AI-enabled quality improvements very important or essential, with nearly a third expecting to reconsider provider relationships within the next 12 months because of this.
Some of the at-risk work is worth over $1 million in revenue. So, to protect that revenue, firm leaders need to show clients how they are using AI to improve responsiveness, consistency and value without compromising trust.
AI Is Changing What Good Client Service Looks Like
For years, firms have discussed AI in terms of attorney productivity: How much faster can research be completed? How quickly can a document be summarized? How many hours can an AI-integrated workflow save? But efficiency is only part of it. Clients experience AI through the service they receive.
Clients are unlikely to judge a firm by how many AI tools it has deployed. They will judge the results, including a status report arriving nearly instantly instead of days, relevant matter information at their fingertips, faster answers and consistent communication.
Legal administrators are well positioned to bridge this gap. They can connect the operational friction attorneys experience internally with the service problems clients experience externally and help determine where AI can meaningfully improve both.
Three Questions to Guide AI Adoption
- Where does friction inside the firm create friction for clients? Start by mapping a recurring client-facing workflow, such as matter reporting or responding to routine information requests. Identify where work stalls, where information is gathered manually and which steps require legal judgment versus repetitive processing. The best initial AI use cases are often tasks that consume time without benefiting from an attorney’s judgment.
- What would have to be true for us to use AI here responsibly? A policy requiring attorneys to review AI output is not enough. Firms should define what data may enter a tool, which systems are approved, when output requires attorney verification and whether a client’s outside counsel guidelines impose additional restrictions. Governance should be designed alongside adoption, not after it.
- How will we know the client is actually getting more value? For matter reporting, measure turnaround time, corrections and follow-up questions. For information retrieval, track response time and the frequency of incomplete or incorrect results.
Why Waiting Doesn’t Eliminate the Risk
Legal professionals are often risk-averse and for good reason. Poorly governed AI adoption can create serious problems involving confidential information, inaccurate outputs and inconsistent work product. But the risk calculation has changed, and now waiting to adopt also carries risk.
Banning or ignoring AI does not necessarily stop its use. It can push experimentation into personal accounts, unapproved applications and workflows that administrators cannot audit.
A more effective approach is to build AI permissions directly into the systems attorneys already use. A matter record could indicate whether AI is permitted, prohibited or conditional, while restricted matters could trigger warnings or technical controls. That gives administrators real visibility and control, rather than trying to preserve an AI-free environment that no longer exists in practice.
Clients are unlikely to judge a firm by how many AI tools it has deployed. They will judge the results.
Firmwide policies are only the baseline. One client may prohibit confidential information from entering certain AI systems, another may require disclosure and another may expect technology-enabled efficiencies. Embedding those outside counsel guidelines into the workflow itself, rather than relying on attorneys to recall each client’s requirements in the moment, turns a policy into something enforceable rather than aspirational.
The firms that navigate this transition successfully will not necessarily be those that adopt the most AI tools or move the fastest. They will be the firms that can explain what they use, why they use it, how they protect client information and what difference it makes to the service clients receive.
The old wait-and-see approach assumed the cost of waiting was mostly internal inefficiency. With AI, that calculation has changed. Today, the client may be the one keeping score.
