tldr at bottom
Biglaw Firm Will Pay Associates To Be Bad At AI For A While (100 Hours, To Be Precise)
It's the only way to learn AI, and this firm has figured that out.
There’s a chasm between understanding how to ask the free version of ChatGPT to punch up your emails and building a useful AI workflow. A couple weeks ago, I went to a conference with a panel titled “The Attorney’s Guide to AI” that was supposed to open lawyers’ eyes to building skills and deploying agents, but had to pivot to “so, you type in ‘c-l-a-u-d-e-DOT-a-i’ and enroll in a paid account.” For a change, this isn’t just a case of lawyers being hopelessly behind the curve on technology. The AI industry that needs to produce $6 trillion in revenue by 2030 to stay afloat only musters about $200 billion right now, mostly because the 98 percent of the public doesn’t see anything about AI to justify paying more than… nothing.
But for lawyers who understand how to elevate AI from the free sample platter to something that can provide actual value, they need time to experiment. The message from that same panel mentioned above was that every lawyer needs to start playing around, building skills, running tests, and figuring out what produces quality output.
Ropes & Gray understands this, and will now let all of its associates count up to 100 hours of AI experimentation toward their billable targets. It expands last year’s pilot, which allowed first-years to put up to 400 of their 1,900 hours toward playing with the robots.
This is the right call whether you expect generative AI to become the future of the profession or an ultimately minor productivity lift. Whatever the merits of the technology, moving into the world of skills, agents, and vibecoding is disorienting and the only cure is setting aside time to experiment with it. Whatever the plan, it’s going to fail in some spectacularly unexpected way on the first attempt. But if users keep iterating with the tool, it really does get better.
Just like a first-year associate.
One Ropes associate told Reuters, “you’re investing a lot of time in it and you’re not seeing a ton of efficiencies at first.” That might be an understatement. Horror stories of hallucinations and sloppy drafting tend to arise from practitioners trying to use cheap AI as an “Easy” button. Vendors building professional legal tools have done a lot of work to tailor it to a lawyer’s workflow. And it really is about “workflow.” Even if the technology provides accurate results out of the box, that doesn’t matter much if the way it does this robs the lawyer of meaningful judgment. The human brain can’t move faster and if the AI process isn’t giving the lawyer the necessary time to get the optimal as opposed to bare minimum result, that’s a workflow problem better addressed before it becomes the client’s problem. With individual tweaking, it can get even better.
As long as attorneys don’t become stereotypical “screamer” partners.
This policy generated some snide criticism, with many tying the move to recent reports that the big AI providers — especially Anthropic — have leaned on religious leaders to accept their belief that AI may be a conscious life form. Which is of course goofy.
That said, people who thrill in abusing AI have more than a little of that “serial killers always start out abusing animals” energy. Along with terms like “clanker,” which seem to flirt with people seeking the dopamine hit of using racial slurs without actually using any, there may be reason to crack down on treating AI as a sandbox for humanity’s worst impulses beyond whether it’s sentient or a fancy word calculator. And for the record, it’s the latter.
Look at me going off on tangents again.
Unfortunately, the billable hour treats experimentation as a personal failing. Any associate who wants to commit a Tuesday afternoon to building skills knows they’re losing time. Like sands through the hourglass so are our bonus targets. Giving associates time to learn AI without sacrificing their compensation will pay dividends down the road. It’s a mechanism that Ropes has deployed in the past, like when it let associates bill up to 100 hours for diversity and inclusion work. Of course, that was in 2021… before they deleted all the DEI info from their website to avoid offending the Trump administration.
Akerman has a more formalized process for giving credit for AI experimentation. At Akerman, playing with AI is another assignment that associates can pick up.
Either way, these firms are making an investment. While the AI cult wants you to believe the technology will soon replace 100 percent of attorney hours, the reality is probably somewhere between 5 and 20. Using the Ropes model, 100 hours is about 5 percent of a 1,900-hour target, so if the firm believes that well-oiled AI can boost productivity even 6 percent it’s worth it.
Put aside building and customizing with AI, the proliferation of AI tools requires some experimentation. We’re entering the kitchen sink era when it comes to AI tools. Firms are now willing to buy competing products and let teams and individual lawyers sort out their preferences. Beyond competition, products are announcing MCP connections to complementary products every day, creating a network of warp tubing like a Super Mario Bros. level. Figuring out which user interface the lawyer prefers to do all their work in is an experiment in itself.
For now, these programs represent an exception rather than the rule. But every firm planning to get serious about AI has to come to grips with the fact that this tech isn’t going to optimize itself. Lawyers need time to make it suit their style.
Earlier: The Grace To Dabble: Two Biglaw Firms Look To An AI-First Future
Agentic AI And The QWERTY Problem
he Grace To Dabble: Two Biglaw Firms Look To An AI-First Future
Both firms are investing real resources and forgoing billable hours. They are walking the walk.
Lots of questions swirl around the use of AI by lawyers in general and young lawyers in particular. The questions all center around how do we train young lawyers to use AI tools safely and proficiently while ensuring they develop the skills firms want them to have?
At least two leading firms have recently taken affirmative steps to do just that and prepare for a future where proficiency in the use of AI tools will be critical. Both firms have elected to make an investment in the future that we often don’t see in the legal community. Both firms have elected to forgo some billable hours and perhaps revenue for future returns. Both firms aren’t just talking professional development for young lawyers, they’re investing real resources and forgoing billable hours. They are walking the walk.
The Ropes & Gray Initiative
The first is Ropes & Gray, headquartered in Boston. Ropes has over 1,500 attorneys with 16 offices worldwide and is an Am Law 50 firm. Definitely qualifies as Biglaw. Ropes has decided to make a sizeable investment in AI: starting immediately, first-year associates can spend up to 400 hours of their annual 1,900-hour billable hour requirement for AI training and experimentation. This can include time experimenting and working in groups. That’s up to 20% of the total requirement. The time, of course, can’t be billed to clients.
According to Amy Ross, Chief of Attorney Talent, and Jane Rogers, Partner & Co-head of the Finance Practice, the associates will work in mentoring circles to discuss how they have used AI, what success they have found and importantly what opportunities they have identified. The associates will also receive hands on training. “Associates are expected to co-create solutions, act as thought partners, and help establish repeatable, defensible approaches for applying AI in practice.” The associates will use Ropes’ 15+ approved AI tools. The firm also plans to “collect analyze and disseminate use cases to enhance learning,” say Ross and Rogers.
It’s a good investment with little downside. On the face of it, it looks like Ropes is giving up a chunk of revenue from the 400 hours that the first-year associates could perhaps bill. I say perhaps because that’s not necessarily true. Let’s face it, first-years are not terribly profitable. They lack the experience to do a whole lot substantially.
In Biglaw, they are highly paid but often don’t produce a lot of revenue. Nor are they expected to. It’s a training period. Add to this the fact that lots of clients are simply unwilling to pay for work by beginning associates. So Ropes’ loss or revenue may not be that significant
But the revenue analysis is not the whole story. Retaining associates these days is an arms race. Keeping associates happy is important: a firm may spend a year training a first-year associate and not getting much return only to see them leave and lose the investment. My guess is Ropes’ first-year associates will embrace this program, encouraging their long-term and short-term loyalty.
So, all in all, it’s a smart move that will result in AI-first lawyers that are more productive and happier in the long run. And that will inure to the firms’ benefit long term.
The Grace to Dabble
As I recently discussed, mastering GenAI simply requires taking the time work with it, to try and fail. It requires on the job training more than classroom instruction.
I recently did a podcast interview of Thomas Suh, a former practicing lawyer and founder of LegalMation, an AI litigation tools provider. In his former life as a lawyer, he helped build what he called a tech-first law firm. He and his partners did that by giving themselves the grace to “dabble” as he put it. To master tech by doing what I just said: experimenting, trying different things. Yes, it takes time. Yes, much of that time can’t be billed. But the returns can be significant. Ropes has just given its first years the power to dabble and learn how to leverage AI tools. I’m guessing the return will be significant.
The Latham Program
While Ropes focused on individual experimentation, another Am Law behemoth took a slightly different approach.
A second AI training initiative that will pay off long term is that of Latham & Watkins. Latham is a Los Angeles-based firm and even bigger than Ropes. It has over 3,500 attorneys and over 25 offices worldwide. It consistently ranks near the top of the American Lawyer Am Law revenue rankings. Definitely big, Biglaw.
According to a recent article in Business Insider, Latham took the unusual step in 2024 of bringing all 400 of its first-year associates to Washington, D.C., for a mandatory two-day AI Academy. The program focused on the use of Harvey and Microsoft Copilot and included outside speakers. Latham repeated the program this year.
In addition to the two-day inaugural program, Latham says there are also multiple events and training programs throughout the year aimed at different groups. The program is “designed to equip lawyers to navigate the significant changes that artificial intelligence (AI) will bring to businesses across industries and around the globe,” according to a Latham announcement.
Like Ropes, Latham views AI as a “generational opportunity” according to one of the Latham partners interviewed for the article. And like Ropes, rather than wringing its hands about what the future will be like, it’s leaning in and making an investment in the future. No doubt those 400 associates left the Academy emboldened to use the AI tools and begin their experimentation as well.
Where Does That Leave Others?
Two Biglaw firms. Two similar approaches. I like the Ropes approach since it encourages experimentation and innovation on an ongoing basis. I like the Latham approach because it sets up the guardrails and expectations.
But either way, approaches like these will position these firms for greater success and help them define what Suh would no doubt call an AI-first approach. Both firms seem to get it: AI is going to fundamentally change the practice of law
Too many firms are doing the opposite: wringing their hands about the future while doing little. Trying to drive forward by looking in the rear-view mirror.
What these two firms are doing is a bit unusual. Investing substantial time and energy in non-billable programs that will aid the firms long term, not just this year. In an industry where partners obsess over utilization rates and billable hour quotas, these firms are making a counterintuitive bet that the short-term sacrifice will yield long-term competitive advantage.
Deal With It
And you don’t have to be an Am Law 50 firm to take the reins. It requires a commitment by firm leadership no matter what the firm size to see and plan for a potentially different future. It requires a senior management that itself is willing to learn. A 50-lawyer firm can’t bring 400 associates to Washington, but it can dedicate Friday afternoons to AI experimentation or partner junior associates with tech-savvy partners. Assuming of course that there are partners willing to become tech savvy.
Moreover, in a world where competition and retention of quality associates becomes more difficult every day, firms that treat AI training as optional professional development are setting themselves up to lose talent to competitors who embrace it as core competency.
Want to compete with Ropes and Latham in years to come? Stop wondering if AI will disrupt the practice of law and start developing the talent to deal with it.
Stephen Embry is a lawyer, speaker, blogger, and writer. He publishes TechLaw Crossroads, a blog devoted to the examination of the tension between technology, the law, and the practice of law.
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TLDR
TLDR: Two articles, a year apart, describe how big law firms are making AI learning part of lawyers’ paid working lives. The distinction is between an intensive introduction for new lawyers and ongoing experimentation across a broader workforce.
| When / article | Firm and place | What actually happened |
|---|---|---|
| 2025 article, describing an academy launched in 2024 and repeated in 2025 | Latham & Watkins, described as Los Angeles–based; training held in Washington, D.C. | Brought roughly 400 first-year associates together for a mandatory two-day AI Academy, focused on Harvey and Microsoft Copilot, with additional training throughout the year. |
| November 2025 article | Ropes & Gray, headquartered in Boston | Allowed first-year associates up to 400 hours of their 1,900-hour annual target for AI training and experimentation. Included mentoring circles, hands-on instruction, and sharing useful approaches across the firm. |
| October 2026 article | Ropes & Gray, expanding eligibility across its associate ranks | Allowed all associates up to 100 hours toward annual billable targets for AI experimentation. The article presents this as an expansion of the earlier initiative; it does not clearly establish whether first-years retain their separate 400-hour allowance. |
These are credits toward internal work targets—not AI training charges sent to clients. Pasted text(20261015-052527)
The useful comparison: Latham’s academy creates a common starting point: tools, expectations, and instruction. Ropes’ protected hours create room for repeated practice on actual workflows. Those approaches could complement each other well: a two-day course gets people started; months of experimentation help them become proficient.
The development across years: The 2025 story emphasizes shaping the incoming generation of lawyers. The 2026 story broadens the effort to existing associates. That suggests AI proficiency is becoming an expectation across the workforce, although the articles don’t establish how consistently lawyers participate.
My MBA take: The strongest idea is the incentive change. Telling associates to innovate while judging them by billable hours makes experimentation personally costly. Giving credit removes that conflict. But both writers are enthusiastic about the investment without showing measured returns—no before-and-after productivity, quality, profitability, or retention data. We have concrete organizational commitments, with their business payoff still unproven in these articles.
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TLDR 2 (ME)
Yes—I could read the post through the search index, although the direct page wouldn’t load. There’s a stronger connection to the law-firm articles than simply “professionals must learn new technology.”
Your May 2026 post follows your own progression from Index Medicus, handwritten references, and photocopying, through librarian-mediated searches, to PubMed and downloadable articles. You then connect that history to legal research, digital film editing, and word processing. The underlying intellectual work rests on an infrastructure that keeps changing. bqwebpage.blogspot.com
Here are the connections I find most interesting:
1. The eventual benefit may be more ambitious work, rather than the same work done faster.
Consider a hypothetical literature review: easier retrieval might let someone examine 150 relevant papers instead of 30, follow unexpected connections, and revise the question. The project could take just as long while becoming substantially better. Likewise, AI-trained lawyers might investigate more alternatives or test more arguments. “Hours saved” could miss much of the return. That qualifies my earlier emphasis on the articles’ missing productivity measurements.
2. Your film-editing analogy is particularly revealing.
When revision becomes cheap, people can try versions they previously would never have attempted. Applied to legal or consulting work, the benefit could include exploring three competing explanations, restructuring an argument, or asking how an opponent would attack it. Experimentation changes the finished product—not merely its production time.
3. The firms are funding the transition between infrastructures.
Ropes’ protected hours acknowledge that a capable professional can temporarily become slower while learning a new way of working. Latham’s academy supplies an initial shared vocabulary. Your decades-long account makes those initiatives look like deliberate management of a familiar historical transition.
4. There is also a consequential difference.
PubMed mainly changed access to other people’s intellectual work. Generative AI can propose the synthesis, interpretation, and prose itself. That brings the tool much closer to the professional’s judgment. Learning to evaluate its contribution becomes part of learning to use it.
The surprising implication: We should ask not only, “Did those 100 training hours save 100 hours later?” but also, “What work became feasible—and what level of work will clients eventually expect?” Your historical examples suggest that the standard of an adequate professional work product can rise along with the tools.
