Share
"Learn AI" has become one of the most repeated pieces of career advice in law school career-services offices, and one of the least useful. It's vague enough to mean everything and specific enough to mean nothing, which leaves students with a real question and no real answer: what, exactly, is a firm looking for when it says it wants candidates with AI experience? As it turns out, the data got a lot more specific this year—and the answer is different than most students assume.
The Numbers
Start with what firms are actually doing, not what they're saying in recruiting brochures. According to SurePoint's 2025 State of the Legal Industry Report, covered by The Global Legal Post, lateral associate hiring within the "AI specialism" grew 106% in a single year—outpacing growth in both partner and counsel recruitment. That's not incidental to the broader shift toward lateral hiring generally (lateral associates now account for 51% of Am Law 200 associate hires, the third time in five years laterals have outnumbered entry-level grads). Firms are explicitly building AI-dedicated teams and prioritizing candidates who already have some experience with the technology, in part because their clients are grappling with AI's effects on copyright, privacy, and liability in realtime.
That's consistent with what's happening at the ground level, too. A 2026 Legal Industry Report from legaltech vendor 8am, discussed in a sponsored post on the Texas Bar Blog, found that 69% of surveyed legal professionals now personally use general-purpose AI tools like ChatGPT for work, up from 31% the year before—and firmwide adoption reportedly more than doubled over the same period.
The Relevant Skill is Judgment
In July 2024, the ABA's Standing Committee on Ethics and Professional Responsibility issued Formal Opinion 512, its first formal guidance on generative AI, built around existing Model Rules. The opinion states plainly that lawyers using generative AI tools must "fully consider their applicable ethical obligations," including duties to provide competent representation, protect client information, communicate with clients, and charge reasonable fees. Model Rule 1.1 (Competence) requires lawyers to understand "the benefits and risks associated" with any technology they use to deliver legal services—not just how to operate it, but where it can go wrong.
For a student, the practical translation is this: being able to explain why a lawyer can't hand judgment over to a tool—citing the actual competence and candor obligations involved—is a strong answer in an interview. It's also something any student can prepare, regardless of whether their school has a dedicated AI lab or a single elective on the subject.
What Happens When You Get This Wrong
In January 2026, the Appellate Division of New York's Third Department decided Deutsche Bank National Trust Co. v. LeTennier, which the court itself described as "the first appellate-level case in New York addressing sanctions for the misuse of GenAI." The underlying foreclosure dispute was unremarkable. What made it notable was that the defendant's filings—across five separate submissions—contained 23 fabricated case citations, several with invented holdings attached to real case names. Defense counsel "reluctantly conceded during oral argument that he used AI in the preparation of his papers" and, even after being caught, estimated that 90% of his citations were accurate—a defense the court called "unacceptable by any measure of candor to any court," regardless of whether the number was true.
The court ultimately imposed $7,500 in sanctions against defense counsel and an additional $2,500 against the client personally, and was explicit that the ruling wasn't a verdict against AI itself: generative AI, the court wrote, "represents a new paradigm for the legal profession, one which is not inherently improper," with real potential to expand access to justice and reduce costs.
The Bottom Line
Firms are recruiting for AI fluency, but that means quite a bit more than simple familiarity with the available tools. A student who can point to something they've built or studied, articulate the specific professional obligations that govern AI use in practice, and name what happens when that judgment fails is the sort of candidate firms are looking for.
Share
