According to Fortune, Nandan Nelivigi, a partner at global law firm White & Case with 30 years of experience, has watched automation gradually transform first-year associate work for decades. Now generative AI and AI agents are accelerating this shift dramatically, raising fundamental questions about what entry-level lawyers and accountants should actually do. The impact is already measurable – 81% of knowledge workers have used AI to start or edit their work, yet only 22% of employers have adopted clear AI strategies. Current hiring patterns haven’t shifted much, with first-year attorney hiring at record levels and accounting firms struggling to find enough entry-level talent. But the real crisis is in training – firms must completely reinvent how they develop young professionals when AI handles traditional apprenticeship tasks.
The apprenticeship model is broken
Here’s the thing that really worries me about this shift. The traditional way young lawyers and accountants learned their craft – by doing tedious document review, taking meeting notes, observing senior colleagues – that’s disappearing fast. And those weren’t just tasks to be completed. They were learning opportunities disguised as work. When an AI agent can do in seconds what used to take a junior associate days, what replaces that hands-on learning? Nandan Nelivigi nailed it when he said a lot of the process now happens on personal screens rather than in conference rooms where people can observe. So we’re losing something crucial in professional development.
The hiring paradox
Now here’s what’s really interesting – despite all this automation talk, hiring for entry-level positions in these fields remains strong. Law grad hiring is actually at record levels, and accounting firms are desperate for talent as older CPAs retire. But there’s a disconnect happening. Firms are hiring young professionals, then throwing them into an environment where 81% are using AI tools but only 22% of employers have clear strategies for how to train them with these tools. That’s a recipe for developing professionals who can use AI but don’t understand the underlying reasoning. Basically, we’re creating button-pushers instead of critical thinkers.
Business models have to change too
And let’s talk about the elephant in the room – billing models. The traditional law firm model of charging hundreds per hour for junior associate work? That’s becoming unsustainable when AI does the same work in seconds. We’re heading toward value-based pricing and subscription models whether firms like it or not. In accounting, the shift is even more dramatic – as AI handles manual tasks and complex analysis, firms will need to move beyond financial reviews into business forecasting. The young professionals entering these fields today will be the ones defining these new business models. They’re not just learning the profession – they’re redesigning it.
The coming training revolution
So what’s the solution? Firms need to completely reinvent on-the-job training. It’s not enough to just give young professionals AI tools and hope they figure it out. We need structured programs that teach them to validate AI outputs, spot errors, and develop the cognitive reasoning that used to come from doing the work manually. The good news is that the rising generation of AI natives can actually help their senior colleagues see new possibilities. But this requires conscious effort – managing and mentoring must now account for both people and technology. Firms that get this right will thrive. Those that don’t? They risk having no next generation of leaders.
The accounting profession faces particular challenges here – the 2025 accountant shortage is real, and AI could either exacerbate it or help solve it depending on how firms approach training. The key insight from all this? We’re not replacing young professionals with AI – we’re creating a partnership. But that partnership requires completely new thinking about how knowledge gets transferred from one generation to the next. The old apprenticeship model is dead. Long live whatever comes next.
