Who Trains the Next Manager When AI Does the Junior Work?

AI is becoming remarkably good at work traditionally assigned to junior employees. Research, analysis, drafting and routine problem-solving are increasingly handled by systems that can complete assignments in minutes.

That creates an attractive productivity opportunity. It also raises a management problem that deserves more attention.

If AI takes over the work through which employees traditionally gain experience, how do we develop the next generation of managers and specialists?

Two developments from the past week bring that question into sharper focus.

Anthropic Puts Equity Behind the Problem

On Sunday, Anthropic announced plans to commit 5% of its shares to a new Public Benefit Fund, subject to stockholder approval.

The fund could eventually receive additional equity as the company’s valuation increases. Anthropic says the money may support nonprofit organizations, direct assistance to affected populations and initiatives addressing the broader consequences of AI.

One area the company specifically identified is employment.

Anthropic has already committed $200 million to studying and addressing AI’s effects on the labor market. The new fund would give it considerably more flexibility to pursue those efforts.

The details of how the fund will operate are still being developed, and the company has not established precisely how the money will be distributed.

Still, the announcement is significant. One of the companies developing increasingly capable AI systems is proposing to dedicate part of its future economic value to addressing the disruption those systems may create.

That is an unusual approach to corporate responsibility, particularly for a technology company preparing for a public offering.

The Career Ladder Is Changing

Last week, the International Monetary Fund published new research examining approximately 40 million online job postings across 19 Asian economies.

The researchers found that employer demand in occupations more exposed to AI had declined by nearly 10% relative to less-exposed occupations.

Importantly, the IMF also found signs that the effect had stabilized, suggesting AI is changing the composition of work rather than simply eliminating entire occupations.

During the IMF and World Bank meetings in Bangkok, Managing Director Kristalina Georgieva raised a related concern.

Many young workers begin their careers performing routine assignments. Those assignments help them develop the judgment and experience needed to advance.

AI is becoming capable of performing much of that work.

Consider a junior financial analyst who traditionally spends time assembling reports, investigating discrepancies and preparing recommendations for review.

Those assignments teach the analyst how the business works. They also create opportunities for experienced colleagues to provide feedback.

An AI system might now produce the initial analysis in seconds.

The company gains efficiency, but the employee may lose an important part of the learning experience.

This doesn’t mean businesses should preserve inefficient work simply because it has historically served as training.

It means the development of employee judgment may need to become more intentional.

Junior employees could spend less time preparing information and more time evaluating AI-generated work, investigating unusual results and participating in decisions alongside experienced colleagues.

That could accelerate professional development if managers approach it deliberately.

It could also leave employees with impressive technology skills but limited understanding of the businesses they’re supposed to manage.

Strategic Perspective

I find Anthropic’s announcement encouraging. The company is acknowledging that AI’s economic benefits and its effects on employment deserve consideration together.

But businesses have a more immediate responsibility.

As we introduce AI into everyday operations, we should pay attention to which assignments historically helped employees develop expertise.

The goal is to give people more valuable experience earlier in their careers, using AI to accelerate their learning.

For an owner or executive, that creates a useful question.

If AI now performs much of the work your junior employees used to do, what experiences are replacing it?

A good answer could produce better-trained employees, faster advancement and stronger organizations.

And that would be a productivity improvement worth pursuing.