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Chronicles

The story behind the story

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On-the-job learning in fields like law and banking faces a double threat: hybrid work limiting juniors' time with seniors and Gen AI cutting many routine tasks

Employers will have to be more deliberate in the training they offer junior staff  —  Jamie Dimon is unequivocal about the impact …

Financial Times Emma Jacobs

Context & Ripple Effects

Professional-services employers have long relied on routine work and proximity to senior colleagues as an informal training system. This warning identifies two simultaneous breaks in that system: less in-person observation and fewer entry-level tasks on which to build judgment.

It foreshadows later coverage of firms redesigning entry-level hiring and training around AI and evidence that AI-native recruits may require more careful oversight when using AI tools. The issue is not simply junior headcount, but whether firms can still develop the next layer of experienced practitioners.

First-order effects

  • Junior staff in law and banking lose both day-to-day access to senior colleagues and routine assignments that traditionally supplied repetition, feedback, and context.
  • Employers must replace incidental apprenticeship with more deliberate training, supervision, and task design for junior roles.

Second-order effects

  • Managers and senior professionals may spend more time reviewing AI-assisted work and teaching judgment, reducing some of the productivity benefit from automating routine tasks.
  • Firms that continue to hire juniors will face pressure to distinguish training roles from work that can be automated, alongside the broader risk of AI-driven reductions in bank staffing identified in global-bank job-cut forecasts.

Third-order effects

  • If firms automate junior work without rebuilding apprenticeship, professional services could develop a thinner pipeline of mid-career talent with the practical judgment that senior roles require.
  • The durable competitive question shifts from AI access to institutional capability: which firms can combine AI efficiency with credible training, oversight, and career progression.

The trend: This is part of AI industrialization in knowledge work, where firms must redesign the talent pipeline as automation and hybrid work weaken traditional apprenticeship.