Beyond Efficiency: What 124 Law Firm Associates Are Telling Firm Leaders About Legal AI
AI Summary
Litera, ALM, and Law.com surveyed 124 law firm associates about Legal AI and associate development. At most firms, efficiency is the whole story, even though it's the smallest part of the return. The full return on Legal AI investment, what Litera calls RoAI, counts efficiency alongside the deeper client relationships and new revenue that freed-up time can fund. Firm leaders will find where AI adoption breaks down, what associates want from it, and how to measure whether it's working.
TL;DR
- Litera's RoAI framework measures the full return on Legal AI investment: the efficiency it creates, the deeper client relationships that freed-up time builds, and the new revenue those relationships can generate.
- 74 of 124 associates expect AI to augment their work, yet 76 say efficiency is the dominant story at their firm, so most firms are underselling what associates are ready for.
- 68 of 124 associates get under an hour of partner coaching a week, and most firms have no rubric to measure whether AI use is making anyone a better lawyer, leaving the tools underused.
In This Article
- What Does Legal AI Deliver Beyond Efficiency for Law Firms?
- What Law Firm Associates Think About AI
- Why Aren't Law Firm Associates Using Legal AI Tools Effectively?
- Is Legal AI a Risk to Associate Skill Development?
- How Do Law Firms Measure Return on Legal AI Investment?
- Building Legal AI Training Programs That Last
- Frequently Asked Questions
What Does Legal AI Deliver Beyond Efficiency for Law Firms?
Beyond efficiency, Legal AI delivers what Litera calls Return on AI Investment, or RoAI. Alongside the time saved on routine work, RoAI counts the deeper client relationships earned with the hours AI frees up and the new revenue from expanded matters and new business those hours can build.
Time saved is easy to celebrate, and it's also the easiest number to mistake for the whole story. When AI compresses legal work, billable hours shrink with it, and a firm that invests in speed without a plan for growth can end up with less revenue than it started with. That's the problem RoAI addresses.
Solving that requires a platform built for both sides of the equation — the practice of law and the business behind it. Litera is the only Legal AI platform that addresses both. That's why 99% of the Am Law 200 trust it, and why the RoAI conversation starts here.
What is RoAI for law firms?
RoAI stands for Return on AI Investment. Where most AI metrics stop at hours saved, RoAI tracks three interconnected outcomes: efficiency gains from automating routine work, relationship depth from reinvesting recovered time into clients, and revenue growth from the expanded and new business that stronger relationships produce. Time saved and time reinvested are two different business outcomes, and RoAI measures both.
What Law Firm Associates Think About AI
To understand how Legal AI is landing inside law firms, Litera partnered with ALM and Law.com to survey 124 associates across junior, mid-level, and senior roles. These are the lawyers closest to the work AI is changing, and their answers cut against the dominant narrative at most firms.
74 of 124 associates expect AI to augment their work, and another 30 expect it to accelerate their development. Only 12 think it will replace them.
The disconnect is in the message. When asked about the dominant AI story at their firm, 76 of 124 associates said it was efficiency, and only 13 said their firm frames AI as something that speeds development. Associates want the bigger conversation, and most firms aren't having it.
The way associates build legal skills is changing, and the firms that recognize that shift earliest will have a meaningful development advantage.
Josephine Kenny, Director of Client Value and Innovation at Litera, recalled spending weeks reviewing contracts as a junior lawyer. With AI, she said, you can see hundreds of versions of a clause at once and "learn from the machine." The exposure that once took years now takes minutes. Firms that treat that shift as a training opportunity will develop sharper associates faster than those still waiting for the old ramp to work.
Why Aren't Law Firm Associates Using Legal AI Tools Effectively?
Law firm associates aren't using Legal AI tools effectively because most firms stopped at deployment. Most associates don't have enough time to learn their firm's AI tools, and 68 of 124 get less than one hour of partner coaching a week. Buying licenses and building a training culture are two different investments, and most firms have only made one of them.
How big is the AI training gap at law firms?
55% of associates say they only somewhat have time to learn their firm's AI tools, and another 18% say they have no time at all. When three-quarters of associates can't engage meaningfully with the tools their firms have deployed, self-directed learning isn't a realistic substitute for structured training. The firms closing this AI skills gap are the ones that treat associate AI training as a workday commitment, the same way they treat billable hour targets.
Why measurement is a hidden law firm AI adoption gap
Roughly 75% of associates are at firms with no standard way to measure whether AI is working, and most of what does get tracked stops at seat utilization. Knowing how many licenses are active tells a firm nothing about whether those tools are making anyone a better lawyer, which makes it a difficult investment to defend and an even harder one to improve. Without measurement, AI training is optional in practice even when it's required in policy.
Is Legal AI a Risk to Associate Skill Development?
Legal AI is a risk to associate skill development when the underlying model isn't accurate enough to learn from. 43% of associates name output quality as their top concern, 20% worry about weaker critical thinking, and 15% fear losing drafting and research skills. Those concerns are legitimate, and they point directly at the difference between legal-specific AI and general-purpose models.
What most firms don't account for is how much time associates currently spend on work AI can already do. 36% say it takes one to two years to move from clause identification to substantive legal analysis, and another 17% say two to three years. More than half of associates spend over a year on mechanical review before reaching the work that develops their judgment. Accurate Legal AI compresses that timeline so associates get to the harder, more formative work sooner.
Litera's proprietary redline algorithm runs 100% more accurate than general-purpose LLMs, and Kira's contract intelligence covers 1,400 fields trained on 45,000 lawyer hours across 50 jurisdictions. Associates who can trust what they're reviewing can focus on interrogating the output rather than second-guessing it, and that's where the real legal development happens.
No AI startup can shortcut 30 years of legal-specific learning, and newer entrants that look compelling in a demo often underdeliver when the work gets complex. Patrick Grant, Associate Professor of AI and Technology at The University of Law, put it plainly: "There is never going to be a time a lawyer doesn't need to be a lawyer."
How Do Law Firms Measure Return on Legal AI Investment?
Hours saved is still the dominant way firms measure Legal AI, and that captures only one part of the return legal leaders should expect. A more complete picture tracks how quickly associates reach substantive work, whether client relationships are deepening, and whether recaptured hours are generating new revenue. Those outcomes map directly to the three components of RoAI.
Measuring those outcomes isn't straightforward, but firms that don't try are making AI investment decisions without knowing whether the last one worked. The survey's retention data adds another dimension. Long hours, burnout, and high workload volume were the top attrition drivers, cited by 63, 63, and 53 of 124 associates respectively. Those are exactly the conditions well-implemented AI can reduce, and firms that pair the right tools with structured training are beginning to see measurable differences in associate retention.
Building Legal AI Training Programs That Last
The survey points to four traits that Legal AI training programs for associates share when they work past launch: clear ownership, embedded tools, real matters, and measurement. Getting all four right means training happens inside live work, where the tool and the task are the same thing.
Embedded tools are what keep adoption alive past the first few weeks of law firm AI implementation. Lito, Litera's award-winning Legal AI agent, works inside Word, Outlook, and Teams, so associates don't need a new login or a new workflow to use it — the tool is already where the work happens.
Without clear ownership, AI adoption becomes a practice group lottery. When one team builds fluency and the next hasn't heard of the tool, the firm's investment compounds in one pocket and disappears everywhere else. Firm-wide ownership of tools, training, and measurement is what keeps that from happening.
Frequently Asked Questions
What is RoAI and how does it apply to law firms?
RoAI stands for Return on AI Investment. It measures Legal AI across three outcomes: the efficiency it creates, the client relationships that freed-up time can deepen, and the revenue that stronger relationships generate. RoAI reframes the central question from how much time AI saves to what the firm does with that time, and only Litera is built to deliver all three.
What do law firm associates think about AI?
In Litera's 2026 survey of 124 law firm associates, 74 expect AI to augment their work and 30 expect it to accelerate their development. Only 12 expect AI to replace them. The majority want their firms to frame AI as a career accelerator, and most firms aren't having that conversation yet.
Does AI replace associate work at law firms?
No. Only 12 of 124 associates in Litera's 2026 survey expect AI to replace them within three years. Associates expect Legal AI to handle routine review while they focus on analysis and judgment. AI changes the composition of associate work at law firms, but it doesn't remove the need for lawyers or the professional judgment behind the work.
What is the difference between AI efficiency and AI growth in legal?
AI efficiency is the time Legal AI saves on routine work. AI growth is what a law firm does with that time: deeper client relationships and new revenue from expanded matters. Litera's RoAI framework measures both together because firms that track only hours saved are capturing less than a third of their return on Legal AI investment.
How should law firms build Legal AI training programs for associates?
Legal AI training programs for associates work past launch when they share four traits: they teach inside real matters, assign clear ownership, use embedded tools, and measure results. Associates build habits from training tied to live matters, and firms that treat associate AI training as a workday commitment rather than a one-time event see meaningfully stronger adoption over time.
How can law firms get lawyers to use AI tools?
The survey data points to two reasons lawyers underuse AI tools at law firms: insufficient coaching time and no measurement framework, neither of which reflects low interest among associates. Firms that see strong adoption train inside real matters, use embedded tools that require no new login, assign clear ownership across practice groups, and track whether usage is improving the quality of legal work over time.
How is Litera's Legal AI accuracy different from general-purpose LLMs?
Litera uses rules-based engines for deterministic accuracy on high-stakes legal work, where a probabilistic answer carries too much risk. Litera's proprietary redline algorithm is 100% more accurate than general-purpose LLMs, and Kira's contract intelligence models were trained on 45,000 lawyer hours across 50 jurisdictions, giving law firms a level of legal AI accuracy that open-web models aren't trained to deliver.
How do you build a law firm AI adoption strategy that lasts beyond launch?
A law firm AI adoption strategy that lasts beyond launch requires four things: tools embedded in existing workflows, training tied to real matters, firm-wide ownership across practice groups, and measurement frameworks that track whether AI is making associates better lawyers. Firms that deploy without all four tend to see strong initial usage followed by steady decline as associates return to familiar workflows.
Go Deeper
The data behind this post comes from Forging the Path for the Future of Law: The Evolving Role of AI in Associate Development — the full report includes complete expert interviews and Litera's analysis of each finding. Read the report.
For the raw numbers, the interactive version lets you explore the complete survey results on your own. Explore the interactive findings.
If you want to hear practitioners work through what Legal AI adoption looks like past the first few weeks, Education and Training in the Age of Legal AI is worth an hour. Leaders from Linklaters, Stanford Law School, The University of Law, and Litera cover what's working and what isn't. Watch the webinar.
