Is AI Destroying Entry-Level Paths to Expertise?

How will the next generation of leaders develop judgment if AI automates the grunt work?


Introduction

The democratisation of AI is creating critical tension in talent development. AI tools have created unprecedented efficiency by automating routine tasks. Yet, they simultaneously threaten traditional paths to expertise.

This phenomenon has been coined the “hollow middle” by experts.  This occurs when entry-level tasks, which were previously the proving grounds of junior employees, are handed over to large language models.

To build a sustainable workforce, leaders require foresight to see beyond immediate productivity, and the long-term structural risks of an AI-dependent workforce must be addressed.

The Quiet Erosion

The erosion of entry-level jobs has moved beyond a theory; it is now a measurable economic shift. This has been confirmed by a 2025 Stanford study titled “Canaries in the Coal Mine”, revealing that employment for early career workers in AI-exposed roles has declined by 13% compared to less exposed roles since late 2022. Conversely, senior roles have remained stable.

This deviates from the traditional layoff cycle. Companies are now simply containing entry-level hiring, anticipating that AI will handle a larger degree of routine work. A 2025 Boston Consulting Group report paints a similar image, revealing that 29% of companies heavily adopting AI expect a reduction in junior roles.

The Knowledge Trap

At the root of this issue lies the critical distinction between two types of knowledge. A 2025 study by Falckenthal et al. finds that AI excels at codified knowledge (i.e. knowledge that is found in textbooks or repositories). Yet despite AI’s continued development, tacit knowledge (i.e., nuance, political savvy and context-specific judgement) is a skill set it struggles to master.

Juniors generally acquire tacit knowledge in two ways. Firstly, by performing codified tasks and understanding their underlying processes. Secondly, by interacting with their seniors, they serendipitously absorb the unwritten rules of the trade.  

If AI continues to remove these learning opportunities, the business world may soon find itself facing a “knowledge trap”.

Entry-level employees often enter the world of work with plenty of theoretical knowledge amassed from years of studying. However, they may soon be denied the opportunity to put theory into practice.

 A 2025 Harvard study by Edmonson and Chamorro-Premuzic found that while AI may increase output by up to 40%, juniors who accept AI suggestions uncritically perform worse than those who reason through problems themselves. Ultimately, without having to face the struggle of putting pen to paper and writing a first draft, the necessary critical thinking skills required to audit the machine are left untrained. Potentially depriving the workforce of future senior employees.

From Doers to Orchestrators

Hence, companies require a reinvention of what it means to be an entry-level employee.

Indeed, the same study suggests a shift towards “red teaming” as a solution. Instead of asking new hires to write reports, they should instead audit AI drafts, identifying weak assumptions, missing data, or logical flaws. Thus, AIs are transformed into sparring partners rather than replacements.

On the other hand, the Boston Consulting Group report proposes the integration of new roles for juniors, such as “integrators” or “orchestrators”. In these functions, rather than being judged on their ability to grind out tasks, they are assessed by their ability to read a whole workflow and coordinating AI tools to achieve the desired outcome.

Bridging the Intergenerational Gap

It is the role of the leader to act as the bridge between the digital fluency of the young and the tacit wisdom of the old.

Falckenthal et al. claim that plugging this gap will enable the creation of intergenerational tandems, wherein AI is a collaborative tool between seniors and juniors:

The senior provides tacit knowledge, the junior operates the AI, and AI accelerates the output.

Ultimately, the hollow middle and knowledge trap are not inevitabilities; they are structural choices. Human skill acquisition must be prioritised as much as algorithmic efficiency to ensure that a future generation of leaders exists.


Sources:

Beauchene, V., et al. (2025, December 15). How Agents Are Accelerating the Next Wave of AI Value Creation. Boston Consulting Group.

Brynjolfsson, E., Chandar, B., & Chen, R. (2025). Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence. Stanford University and NBER.

Edmondson, A. C., & Chamorro-Premuzic, T. (2025, December 11). The Perils of Using AI to Replace Entry-Level Jobs. Harvard Business Review.

Falckenthal, B., Au-Yong-Oliveira, M., & Figueiredo, C. (2025). Intergenerational Tacit Knowledge Transfer: Leveraging AI. Societies, 15(213).

 

 

 

 

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