When Entry-Level Work Disappears: Artificial Intelligence and the Fragile Future of Leadership

Automation is quietly dismantling the apprenticeship that once produced organisational leaders.

For generations, the first job inside an organisation was never merely a job. It was where future leaders quietly learned how institutions actually function.

Fresh graduates entered firms performing tasks that appeared routine: preparing reports, analysing spreadsheets, summarising meetings or documenting processes. Yet these activities were never simply clerical. They functioned as a form of organisational apprenticeship through which newcomers gradually acquired tacit knowledge about how authority operates, how decisions unfold, how teams negotiate disagreements and how organisations function beyond formal charts and policies.

Through routine work, individuals learned the informal dynamics that no manual fully explains.

Today, that apprenticeship is quietly disappearing.

In 2023, Goldman Sachs estimated that generative artificial intelligence could automate work equivalent to 300 million full-time jobs globally. Around the same time, the World Economic Forum reported that 44 per cent of workers’ core skills will change within five years as artificial intelligence reshapes the labour market. These figures are often interpreted as signals of productivity gains and economic restructuring. Yet hidden within them is a quieter organisational shift: the gradual disappearance of entry-level work.

Artificial intelligence is rapidly absorbing precisely the tasks historically performed by early-career professionals.

Large language models can draft business documents, analyse datasets, summarise research, generate software code and prepare presentations within seconds. Many of the activities once assigned to junior analysts, assistants, and associates are now automated into digital workflows. According to the OECD, around 27 per cent of jobs across advanced economies involve tasks highly exposed to automation, particularly routine cognitive work typically performed by early-career professionals.

Recent academic research reinforces this pattern. A study by Erik Brynjolfsson, Danielle Li, and Lindsey Raymond examining generative AI adoption in customer support work found that AI tools significantly increase productivity on routine knowledge tasks, activities disproportionately performed by junior employees. Similarly, an analysis by OpenAI and the University of Pennsylvania estimated that around 80 per cent of the workforce could see at least 10 per cent of their tasks affected by large language models, with administrative, legal and analytical occupations among the most exposed.

The effects are already visible in hiring patterns. In sectors such as technology, consulting and finance, companies are experimenting with smaller graduate recruitment cohorts while expanding AI-assisted workflows. Labour market analyses suggest that entry-level hiring across several professional sectors has declined by roughly 25–30 per cent since the emergence of generative AI tools in 2022, even as demand for experienced professionals remains relatively stable.

What is disappearing, therefore, is not simply a category of jobs but the developmental stage through which organisations historically cultivated their future leaders.

Entry-level roles have long served as environments where individuals learned not only technical skills but also organisational behaviour: working under authority, managing expectations, resolving disagreements and collaborating across teams. These experiences formed the early stages of organisational socialisation through which individuals gradually developed judgement.

Such learning cannot easily be replicated through coursework or automated training systems. It emerges through participation in real organisational processes.

If the first step of organisational life disappears, a deeper question emerges: where will future leaders come from?

Leadership rarely emerges suddenly. It is typically the cumulative result of years spent observing decisions, participating in organisational routines and gradually assuming responsibility. Individuals develop judgment not through abstract instruction but through lived experience-by navigating conflicts, witnessing the consequences of decisions and learning institutional norms over time.

Most senior executives begin their careers in junior roles, where they build a tacit understanding of how organisations actually function.

When these early stages of organisational apprenticeship decline, the leadership pipeline itself becomes fragile. Organisations may possess increasingly sophisticated technological systems, but fewer individuals who have accumulated the formative experiences that cultivate leadership capability.

At the same time, another structural transformation is reshaping the nature of work. Even where entry-level roles still exist, the rise of gig and project-based employment is weakening the long-term organisational attachment through which leadership capabilities historically developed.

Even before generative AI emerged, the model of stable long-term employment within a single organisation had already begun to erode. The expansion of digital labour platforms and freelance markets has accelerated the shift toward portable careers and project-based work. Estimates suggest that more than 1.5 billion workers globally now participate in some form of freelance or gig employment, reflecting the growing fragmentation of organisational labour.

This transformation alters how individuals relate to organisations. Workers increasingly identify with their skills, portfolios or professional networks rather than with a single employer. Organisations assemble project teams that form quickly and dissolve once objectives are completed.

While this model offers flexibility and efficiency, it also changes how organisational culture develops.

Culture is often described in corporate language as values or mission statements. In practice, however, culture emerges through sustained interaction. It forms when individuals work together repeatedly over time, gradually building shared norms, trust and institutional memory. Mentorship relationships, informal networks and long-term collaboration historically allowed organisations to transmit knowledge across generations of employees.

When employment becomes temporary, distributed and mediated through digital platforms, these processes weaken. Teams assemble rapidly but disperse just as quickly. Workers move frequently between organisations, carrying expertise but not necessarily institutional attachment. Organisational culture risks becoming less lived experience and more managerial narrative.

This shift also complicates contemporary discussions about leadership itself. Management discourse frequently emphasises psychological safety, empathy and emotional intelligence as essential leadership competencies. Yet these qualities are not simply individual traits that leaders can adopt through training programmes. They emerge from organisational structure.

Empathy develops when people work together long enough to understand one another’s constraints and motivations. Psychological safety emerges when individuals trust that disagreement will not threaten their place in the organisation. When work becomes temporary, platform-mediated and increasingly coordinated through algorithms, these relational foundations become fragile.

In such environments, the language of empathetic leadership risks becoming mere rhetoric, structurally difficult to put into practice.

Meanwhile, public debate around artificial intelligence sometimes drifts toward speculation about machine consciousness. Technology leaders occasionally suggest that future AI systems may develop forms of awareness. Whether such developments materialise remains uncertain.

Yet a more immediate concern may lie elsewhere: the possibility that organisations themselves become increasingly mechanistic.

As AI systems optimise administrative coordination, data analysis and decision support, organisations may gradually prioritise efficiency over human development. The processes through which individuals gain experience, build judgement and develop leadership capability may receive less attention in highly automated workplaces.

History suggests that societies eventually adapt to technological disruption. The Industrial Revolution displaced agricultural labour but created manufacturing industries. The digital revolution automated clerical work yet generated entirely new sectors of employment. Artificial intelligence will likely produce new forms of work that are difficult to anticipate today.

But transitions matter.

If entry-level opportunities disappear faster than new developmental pathways emerge, organisations may face a generational gap in leadership capability. Institutions that once relied on decades of accumulated experience may find themselves without individuals who have progressed through the formative stages of organisational life.

Artificial intelligence may become increasingly sophisticated.

But leadership is not an algorithmic output. Artificial intelligence may become increasingly sophisticated.

But leadership is not an algorithmic output.

As artificial intelligence becomes more powerful, the critical question may not be whether machines become more intelligent.

It may be whether organisations remain sufficiently human.

Authors: Prof. Moitrayee Das, Faculty of Psychology, FLAME University; & Prof. Shreerang Chaudhary, Faculty, MIT-WPU.