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By Erica Frisby | Marketing Manager, LexisNexis® Legal & Professional At the LexisNexis® AI Symposium panel, “Lawyering in the Age of AI: Preparing the Next Generation for Practice...
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By Erica Frisby | Marketing Manager, LexisNexis® Legal & Professional
At the LexisNexis® AI Symposium panel, “Lawyering in the Age of AI: Preparing the Next Generation for Practice,” the conversation moved quickly past whether lawyers will use AI. That question has already been answered.
Young lawyers are using it. Law students are using it. Clients are asking about it. Firms are testing it, training on it, governing it, encouraging it, and worrying about it, often all at once.
The harder question is what comes next: if AI can draft, summarize, research, analyze, simulate, and review at speed, how should the legal profession train the lawyers entering practice now?
The panel was moderated by Nik Reed, Chief Executive Officer of Knowable®, A LexisNexis Company. He was joined by Hugh Carlson, Chief Executive Officer of Three Crowns®; Alex Denniston, Director of Innovation & Insights at Factor®; and Stefanie Lindquist, Nickerson Dean and Professor of Law at Washington University School of Law®.
Their central question was practical: AI may give junior lawyers earlier access to higher-value work. But what replaces the learning that used to come from lower-value work?
For decades, legal training has relied on a quiet bargain. Law schools taught doctrine, reasoning, and writing. Firms completed the apprenticeship through research assignments, document review, diligence, cite checking, drafting, and close supervision.
That model was never perfect. Some early-career work was tedious or inefficient. But it also taught young lawyers how legal work actually works. They learned to spot patterns, question sources, absorb client context, and develop the skepticism that separates a polished answer from a reliable one.
Reed illustrated the point with a story from a senior lawyer who, as a third-year associate, was asked to deliver his firm’s view during the IPO of The New York Times® after the partner could not attend.
The story landed because it feels almost unimaginable in many modern firms. A third-year associate speaking for the firm in a consequential room. Senior business leaders are waiting for the legal answer. A young lawyer expected not only to know the work, but to own the moment.
That kind of responsibility once came earlier in many legal careers. In many firms, it can feel harder to imagine today. Risk, complexity, and layers of review have changed how responsibility is handed out.
AI may force the profession to revisit that choice. If technology reduces some of the routine work that has filled the early years of practice, could younger lawyers move closer to strategic judgment, client interaction, and responsibility? The opportunity is real. So is the risk. Earlier responsibility only helps if young lawyers are prepared for it. That preparation cannot be accidental. It has to be designed.
Stefanie Lindquist framed the challenge directly. Law schools are the legal talent pipeline for the profession, with obligations both to students and to the employers who need lawyers prepared for AI-enabled practice.
Lindquist put the law school challenge plainly: legal education can no longer treat AI as a question of tool access alone. Students need to learn how to use AI in an organizational, systemic way that helps firms and clients succeed.
That need is already showing up in the gap between legal education and law firm expectations. In Bridging the AI Readiness Gap: What Law Schools and Law Firms Need to Know Now, LexisNexis, how firms are looking for new lawyers who can enter practice with stronger AI fluency, judgment, and readiness for real-world client work.
That does not mean law schools should become product training centers. Tomorrow’s lawyers will still need to read closely, reason carefully, and write clearly. But they will also need to manage workflows, question data, understand risk, and supervise AI-assisted work that may look finished before it is reliable.
Lindquist also noted that legal education has not always centered the client enough. AI-enabled simulations may help change that by placing students inside a negotiation, client intake, cross-examination, regulatory response, or contract review scenario before they are doing that work for real clients.
Hugh Carlson described one example already underway. Three Crowns has worked with Stanford® to develop a cross-examination simulator, giving lawyers and students a way to practice advocacy with an AI-supported witness. Carlson did not present simulation as a cure-all. But he did point to realistic, AI-enabled practice environments as part of the next training model.
For law firm leaders, the question is where these environments should sit: in law school, firm training, practice groups, client-service teams, or all of the above. The firms that benefit most will not be the ones that simply hand lawyers access to tools. They will be the ones that create structured opportunities to practice, make mistakes safely, and learn what good supervision looks like.
The promise of AI in early legal careers is easy to see. It can help junior lawyers move faster, engage with more information, draft more confidently, and participate earlier in substantive work. It can also reduce time spent on repetitive tasks.
But the profession should be honest about the trade-off. Many lawyers became better because of some of the unglamorous work they did early in their careers, even if they would not want to repeat all of it.
“The cost side of the ledger will not be vacant.”
Hugh Carlson, Chief Executive Officer, Three Crowns
That is the caution at the heart of the apprenticeship question. If AI removes low-value work, firms may gain efficiency. Clients may gain speed. Young lawyers may gain earlier access to meaningful assignments. But some of the quiet learning embedded in that old work may disappear with it.
The answer is not to preserve inefficient work for its own sake. It is to identify what that work taught and find better ways to teach it: source discipline, factual patience, pattern recognition, client sensitivity, and the habit of asking, “Is this actually right?”
Alex Denniston brought the trainer’s perspective from Factor’s SenseMaker® Academy. His point was simple: AI is easy to start using, but hard to understand well.
He compared it to a bulldozer. Most people understand what a bulldozer does, even if they do not know how to drive one. AI is often the reverse. Anyone can type into an AI tool and get a response. But many users do not yet understand what the tool is good at, where it fails, or how to move beyond basic drafting and summarization.
That matters because many legal organizations are still treating access as progress. A lawyer who asks AI to draft an email is in a different position from one who can use AI to test an argument, identify gaps in a chronology, prepare for client questions, or structure complex work while knowing what must be checked.
Denniston also described two common mindsets. Some lawyers approach AI as an opponent, trying to prove where it is wrong. Others approach it with curiosity, asking what it can help them see, test, or improve. The second mindset does not ignore risk. It starts from a more productive place.
There is a tempting story about AI and junior lawyers: AI handles the routine work, junior lawyers move up the value chain, clients receive better service, and everyone wins.
There is truth in that story. But it is incomplete.
AI-assisted work can look polished before it is sound. A partner or senior lawyer may receive a memo, chart, summary, or draft that appears organized and persuasive. The surface quality may be high. The underlying reliability may still be uncertain.
Denniston named the issue clearly:
“The verification burden on us as managers and supervisors is going to potentially go up significantly.”
Alex Denniston, Director of Innovation & Insights, Factor
That line should stay with firm leaders. AI does not eliminate supervision. In many settings, it raises the stakes of supervision.
Review may need to cover more than the final document. Supervisors may need to ask: What tool was used? What sources were checked? What assumptions were made? What did the lawyer verify independently? Where did human review change the answer?
For associates and legal professionals, those questions point to a new way to build credibility. The strongest AI users will not be the ones who generate the fastest first draft. They will be the ones who can explain their process, identify risk, validate authority, and show where careful review entered the work.
The panel closed with a mix of optimism and caution, which feels right. Lindquist saw an opening to rethink legal education. Carlson emphasized responsibility. Denniston pointed to the unknowns, including the assumptions the profession may not yet realize it is carrying into the future.
That is the real lesson. AI is not making the lawyer disappear. It is changing what the lawyer must be good at.
The next generation will need to know how to use AI, but that will be table stakes. They will need to challenge it, supervise it, explain it, and decide when not to use it. They will need to understand clients, facts, risk, ethics, and context.
For law firm leaders, AI training belongs inside talent strategy, not just technology strategy. For law schools, the task is to prepare students for a profession where tools change quickly, but professional obligations remain. For young lawyers, the opportunity is to become more than fluent users. It is to become trusted reviewers, sharper thinkers, and better counselors.
AI is not ending legal apprenticeship. It is forcing the profession to rebuild it with more intention.
As legal teams rethink how research, analysis, and workflows should operate in an AI-enabled profession, LexisNexis offers solutions built to help lawyers move faster while maintaining the confidence, control, and judgment the work demands. Explore how LexisNexis can help your firm put AI to work with purpose.