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AI requires a rethink of the apprenticeship model for knowledge professionals 

By
Steve Hasker
Steve Hasker
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By
Steve Hasker
Steve Hasker
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November 13, 2025, 9:06 AM ET
Steve Hasker has been President and CEO of Thomson Reuters since March 2020. Prior to joining Thomson Reuters in February 2020, he was Senior Adviser to TPG Capital, a private equity firm, from August 2019 to February 2020. Prior to that, he was Chief Executive Officer of CAA Global, a TPG Capital portfolio company, from January 2018 to August 2019. Steve served as Global President and Chief Operating Officer of Nielsen Holdings PLC from December 2015 to December 2017 and prior to that served as Nielsen’s President, Global Products from November 2009 to January 2014. Steve spent more than a decade with McKinsey & Company as a partner in the Global Media, Entertainment and Information practice from 1998 to 2009.
Steve Hasker
Steve Hasker, CEO of Thomson Reuters.courtesy of Thomson Reuters

Over his 30-year career in corporate law, Nandan Nelivigihas seen many forms of automation gradually change the tasks assigned to first-year associates. 

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When Nelivigi, now a partner in New York at the global firm White & Case, began his career with a freshly minted Harvard Law degree, he recalls that his duties included taking notes at client meetings. These were learning sessions, as he carefully observed the senior associates and partners plying their skills. And for young lawyers involved in litigation, there was also extensive document-based research. 

Through the decades, some of that first-year legal work has been automated. But now generative AI and AI agents — apps that can perform carefully tailored tasks autonomously — have accelerated the process and brought a new level of efficiency. That raises big questions about what a first-year lawyer can do that AI can’t. Or, for that matter, what the role should be for entry-level people in various other knowledge-based professions, like tax and accounting. 

Automation boosts efficiency and frees professionals to focus on high-value work, like client strategy and consulting. Even entry-level talent plays a role in an AI-enabled workplace by learning to validate AI outputs and to spot any errors in the results.

It’s possible, therefore, that a first-year associate at an AI-enabled law or accounting firm may be able to more quickly perform the tasks once handled by someone with a few years of professional experience. Of course, it will still be crucial that these professionals acquire the full set of human wisdom and expertise that will prepare them to be the leaders of their firms 15 or 20 years down the road. 

After all, simply replacing entry-level workers with AI is not an option — not unless business and society are willing to accept, as the older generation retires, that AI agents will be the sole practitioners in these crucial professions. Few people would  settle for that future.

Law schools and universities with pre-law programs are already thinking about how to train the rising generation for an AI-enabled future. It’s imperative that these new graduates enter workplaces that are also adapting to the AI transformation, if the firms want to remain competitive. Future-ready professional firms are the ones that focus on new forms of mentoring and training.

“A lot of the process with AI is not going to be happening in a big conference room where people can observe how others do it,’’ Nelivigi told us. “It’s going to be happening on your personal computer, on your screen or on your phone. So there needs to be a different approach to conveying some of the basic skills on how people will need to work and be trained — and to train themselves to some extent.” 

The Crucial Questions

Certainly at Thomson Reuters, we spend considerable time wrestling with the same questions that Nelivigi is pondering — and not only for our own hiring and training. We know that our approach to the database tools and advisory services we provide to lawyers, as well as to the tax and accounting professions, needs to consider the future of entry-level roles and training. 

Over the decades, machine learning and various forms of AI have made those services increasingly powerful and efficient. But the advent of agentic AI truly represents a major pivot for those professions — and society more broadly — when it comes to defining career paths. 

So far, the impact of AI on the work of entry-level professionals has not translated to hiring patterns. In law, in fact, hiring of first-year attorneys has recently been at record levels. And in the accounting-related professions, the big challenge continues to be finding enough talent to fill the entry-level ranks as older CPAs retire and young people with the requisite skills opt for other types of work. 

In this year’s edition of our annual “Future of Professionals” report, we surveyed nearly 2,300 knowledge workers and found that 81% have tried using AI-powered technologies to start or edit their work at least once. And yet, only 22% of their employers have adopted and communicated a clear AI strategy. Those numbers indicate that whatever their hiring practices, few professional firms have consciously changed their approach to training entry-level employees in response to their use of AI.

It’s time for those doing the hiring and for the AI natives entering the professions to start thinking strategically. And one thing is already clear: Training and management in this new environment must involve supervising people and AI.

Evolving Business Models 

A common concern I hear from the professionals I talk with is that the increasing use of AI tools by entry-level employees could deter development of their on-the-job cognitive-reasoning education — the new habits of mind that a lawyer or accountant receives by working with senior colleagues. That’s why managing and mentoring must take both people and the new technology into account.

“There’s no question,’’ Nelivigi said, “that we need to focus on new types of specific training to make up for what the young people are losing in the new AI environment.”

The Novices Can Also Teach

The rising generation, to which tools like agentic AI are becoming second nature, have a role to play in helping their senior colleagues see the potential for redefining the future of the knowledge professions. 

In law, that might include new business models in which the billable-hours model gives way to broader strategic services with value-based pricing and even subscription models. Clearly, the tradition at some big firms of charging clients hundreds of dollars an hour for even an entry-level employee’s work is not sustainable when an AI agent can do in seconds what once took a person hours or days to accomplish.

In tax and accounting, meanwhile, as AI takes on more of the automation of manual tasks and the handling of complex analysis and data processing, the business might be defined by moving beyond financial reviews to helping forecast the business future. Today’s entry-level knowledge workers are the ones who’ll be defining — and living — that future.

The one certainty: Any organization that wants to still be around in coming years must re-invent on-the-job training for knowledge professionals. Firms that embrace this shift will strengthen their profession. Those that don’t will risk a future without a new generation of leaders. 

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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By Steve Hasker
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