Legal AI adoption has moved quickly from a side project to a change-management priority for law firms. A 2026 industry report found that legal AI use more than doubled year over year — a clear signal...
TODD FRIEDLICH, DIRECTOR OF AI & INNOVATION, WILLKIE On AI adoption, grounded legal content, and the future of legal technology Spring 2026 | NYC Trust in legal AI is becoming a defining factor...
Artificial intelligence is transforming legal practice, helping law firms improve efficiency, strengthen client service, and streamline everyday workflows. As firms look to gain a competitive advantage...
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Legal AI adoption has moved quickly from a side project to a change-management priority for law firms. A 2026 industry report found that legal AI use more than doubled year over year — a clear signal that firm leaders need a deliberate strategy for guiding its use across their teams, both ethically and responsibly. (American Bar Association)
Schenck Price, a mid-size New Jersey firm competing in the NJ/NY metro market, offers a practical example of this shift. Managing partner John Ursin sees AI as a way to help the firm compete for sophisticated work without becoming a larger institution. As he explains: “AI allows us, as a 100-attorney firm, to provide services more like a firm double our size, using AI to amplify our talent and relationships.”
Integrating AI into daily workflows gives law firms several concrete advantages: stronger research support, less repetitive drafting, better use of attorney time, improved client communication, and a greater ability to compete for sophisticated work. For firm leaders, though, the larger benefit is strategic — AI allows a firm to grow its capability without expanding its headcount.
At Schenck Price, AI is treated as an integrated part of how attorneys deliver better work, not simply a faster way to get through it. As John put it: “AI is not about doing things faster or saving time. It allows us to focus on precision analysis and deliver more comprehensive communication to the client. Ultimately, it is the key to a better work product and better results.”
AI might reduce a common legal task from 60 minutes to 20. That alone is meaningful, but the more important question is what attorneys do with the time they save. It’s critical the remainder go toward the judgment and analysis clients are paying for.
As firms research AI tools and chase the newest, fastest features, a more important question is often overlooked: what kind of firm are we trying to build?
Schenck Price operates in a competitive market where nearby firms are growing through mergers and acquisitions. Its leadership, however, is not interested in growth for its own sake. The firm's strategy is to remain a strong regional player that delivers high-quality work efficiently, with a better value proposition than larger firms carrying heavier overhead. For a midsize firm, AI can support that kind of scale without requiring it to adopt the operating model of its largest competitors.
As managing partner, John feels that pressure directly. “We cannot compete and deliver without the right tools.” The firm has responded by investing heavily in AI adoption and integration, which now serves as a central focus of its strategy.
At Schenck Price, AI has become a requirement for competing and delivering value to clients — and across the industry, it is quickly becoming a similar necessity for law firm decision makers more broadly. AI adoption now factors into conversations about client service, pricing pressure, talent use, risk management, and firm identity. It is no longer simply a line item in the technology budget.
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The legal market often talks about AI in terms of speed. Speed matters, but speed alone is a thin business case for lawyers.
A fast draft that misses critical context is not particularly valuable. A quick research answer that requires extensive rework can end up costing more time than it saves. And a client update delivered swiftly, but built on weak analysis, does little to strengthen the relationship.
Schenck Price takes a different approach. The firm views AI as a way to shift attorney attention away from repetitive, lower-value tasks and toward the analysis, communication, and judgment that build trust and improve outcomes. Used this way, AI can help attorneys work from stronger first drafts, identify issues earlier, and produce clearer client-facing communication. Such benefits compound over time rather than fade.
John connects this approach directly to client expectations. In a recent Q&A, he noted that clients increasingly expect their law firms to use AI on their behalf, and that some clients are already reviewing legal work with AI tools of their own. Firms that integrate AI into daily workflows are, in effect, demonstrating that they understand a client's business goals and budget constraints, not just their own.
The best use cases will vary by practice area. Litigation teams may focus on research, case analysis, and drafting. Corporate teams may focus on document review, recurring agreements, and client communications. Legal operations leaders may look at workflows that reduce repeat effort across matters. The underlying principle, though, stays the same: AI should strengthen the work lawyers deliver, not weaken the review discipline behind it.
Legal AI creates real opportunity, but it also introduces real risk. Firm leaders understand that attorney-client communication, work product, confidentiality, and professional reputation cannot be treated as afterthoughts.
That is why Schenck Price's evaluation process ultimately came down to a single factor: trust.
As John put it, “When it comes to choosing where to invest our resources in the tech space, it boils down to one word: Trust. The market is flooded with legal AI companies who make many promises.”
That sentiment reflects how many law firm leaders are approaching the decision. The market is crowded, and claims are easy to make. Firms need to know whether a given AI platform is grounded in reliable legal content, whether it protects sensitive information, and whether the provider can keep pace as the category continues to evolve.
There is also a professional responsibility dimension. ABA Model Rule 1.1, Comment 8, states that lawyers should stay current with changes in law and practice, including the benefits and risks associated with relevant technology. (American Bar Association) While that is not a directive to adopt every new tool on the market, it is a mandate to understand both the value and the risk involved.
Schenck Price's concerns with AI adoption were practical ones. John said the firm's priority was protecting attorney-client communication and work product, and that it could not risk working with a provider that might fail to keep pace as legal AI continues to develop.
For law firm decision makers, that suggests vendor evaluation should include questions such as:
Firms that ask these questions early will be in a considerably stronger position than those that treat AI selection as a simple feature comparison.
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A law firm can purchase AI tools and still fail to change how its lawyers actually work.
Such failure typically does not stem from a lack of curiosity. With any new tech adoption, there is a gap between having access to a tool and building it into everyday practice. Attorneys need to see how AI fits into the work they already do, under the standards they already follow.
Schenck Price treated training as an integral part of adoption, not an afterthought. John said LexisNexis provided general training at the outset, then moved into practice-specific sessions for smaller group. He credits those tailored trainings with accelerating usage across the firm.
The firm’s success in adoption is consistent with recent research on generative AI and legal analysis. A 2026 study found that a brief training intervention increased LLM usage among law students from 26% to 41% and improved exam performance, suggesting that training can meaningfully affect both adoption and output in legal settings. (arXiv)
The lesson for law firms is straightforward: access is not the same as adoption, and adoption is not the same as productive, embedded use.
Partners and technology leaders need to create conditions that let attorneys test AI on matters that feel relevant, safe, and useful. Typically, this happens by starting with practice-specific examples.
A litigation group may need examples tied to motions, pleadings, case summaries, and research validation. A corporate group may need examples tied to document comparison, clause analysis, and client updates. A trusts and estates team may need workflows built around recurring documents and client explanations.
An impossible goal is to turn every lawyer into an AI expert. Instead, lawyers must be thoughtfully familiar enough with AI that they know when to reach for it, when to question it, and when to set it aside.
John captured that progression well: “Once you trust the product, then we need coaching to integrate AI into our daily tasks.” Trust opens the door, but it’s a deliberate approach with customized training that changes behavior.
For small or midsize firms, AI may be changing what competitive scale actually means.
Large firms have deeper staffing benches, broader infrastructure, and more resources to absorb new technology. Midsize firms, by contrast, often have closer client relationships, lower overhead, and a more defined culture. AI can help protect those strengths rather than erode them.
Schenck Price's experience illustrates how that can work in practice. The firm is embedding practical, verifiable AI to support its attorneys, pursue more sophisticated work, improve client communication, and compete against firms with considerably larger footprints. A midsize firm does not need to match a larger competitor attorney for attorney if it can improve how each of its own lawyers works.
Of course, this does not mean AI can erase the advantages larger firms hold. But smaller and midsize firms now have another way to compete. They can use AI to:
John shared a great example: He points to repeat document production as a core source of inefficiency at the firm. Eliminating that repeated drafting through better workflows, he said, allows attorneys and support staff to focus on the details that matter and produce stronger work product without adding time.
That is where the operational and strategic benefits of AI meet. AI not only speeds up a task, it changes what a firm can promise its clients. And for Schenck Price, that promise is clear: compete at a high level, preserve its regional identity, and continue delivering strong legal services efficiently.
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AI adoption can quickly become vague if leadership does not define what success looks like.
Usage numbers are a useful starting point, but they tell an incomplete story. A firm can have high login rates and still see little real value. It can have enthusiastic early adopters without meaningful practice-wide change. It can save time on one task while creating review problems elsewhere.
Law firm leaders should instead measure AI against the outcomes that matter most to the business. That evaluation should center on five questions:
Schenck Price's experience points in this direction. John said the firm's attorneys trust the platform, use it in daily work, and rely on ongoing support and follow-up training to continue improving adoption.
The benefits of AI in legal practice for law firms extend well beyond speed. For firm leaders, the larger value lies in better work, stronger client service, safer adoption, and greater flexibility to compete.
Schenck Price's experience offers a practical lesson. AI works best when it supports a clear firm strategy, rests on a foundation of trust, receives genuine investment in training, and fits how attorneys already handle research, drafting, communication, and client service.
The firms that benefit most will be the ones who stop chasing every new tool and decide, deliberately, how AI should serve their clients, their attorneys, and their business model. AI can assist the work, but it cannot define the standard a firm holds itself to. That responsibility still belongs to managing partners, practice leaders, and technology leaders.
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