For decades, major consulting firms have operated according to an almost immutable mechanism. A few partners would sell high-value strategic projects. Behind them, an army of juniors produced analyses, benchmarks, PowerPoint slides, and Excel models under extremely tight deadlines. This pyramidal model constituted the economic engine of firms like McKinsey & Company, Boston Consulting Group, or Bain & Company.

Today, this architecture is beginning to waver under the impact of generative artificial intelligence. According to a survey published by Bloomberg in April 2026, major American firms are now modifying their recruitment methods to assess candidates’ ability to work with AI, rather than simply without it. The change may seem subtle. It is actually structural.

The End of the Traditional Junior Consultant Model?

The economics of consulting historically relied on a coherent asymmetry: relatively inexpensive junior profiles performed analytical tasks billed at very high rates to clients. This human leverage logic enabled consulting firms to build substantial margins over several decades.

But generative models are disrupting this equation.

AI can produce in just a few minutes: an industry synthesis, a first draft benchmark, a strategic presentation structure, a basic financial model, or a comparative analysis of public data. In other words, part of the “grunt work” historically assigned to juniors is becoming automatable.

The question is no longer theoretical. It is now operational.

According to The Guardian, McKinsey & Company already uses internal generative AI tools, including an assistant called “Lilli,” even in certain phases of recruitment. Candidates can be assessed on their ability to interact effectively with these systems to solve complex business cases.

The signal is strong: the expected competency is no longer purely analytical. It is becoming hybrid. Consultants must learn to pilot AI agents.

A Silent Transformation of the Entry-Level Job Market

This transformation extends far beyond the consulting sector alone. An article published by Fortune in April 2026 brutally summarizes the situation:

“AI won’t kill your job. It will kill the path to your first job.” The issue is not just the direct destruction of jobs. It primarily concerns the gradual disappearance of entry-level tasks that historically allowed recent graduates to learn their profession.

Economic data are beginning to confirm this trend.

The Federal Reserve Bank of Dallas observes a significant decline in employment among 22-25 year-olds in professions most exposed to cognitive automation. Some studies mention a decrease close to 13% since 2022 in several highly digitized professional categories.

The paradox then becomes obvious: companies continue to seek experienced profiles, but the traditional mechanisms for building that experience are being weakened.

How can we train future seniors if juniors no longer perform the tasks that historically built their discernment?

“Grunt Work” Also Had a Pedagogical Function

In consulting professions, long nights spent building Excel models or producing slides were not just an operational constraint. They also constituted a learning process.

It was through this accumulation of micro-analyses that the following developed: strategic judgment, the ability to detect inconsistencies, understanding of industry dynamics, political reading of organizations, uncertainty management.

AI can accelerate production. It does not automatically transmit tacit experience. This distinction becomes central. Economists are beginning to distinguish between two categories of value: standardizable analytical production and discernment derived from experience.

The former tends to become abundant and inexpensive thanks to AI. The latter could, on the contrary, become rarer and more expensive.

Value Is Shifting Toward Seniors

This transformation is gradually modifying the economic hierarchy of firms.

For a long time, value was captured by the ability to mobilize a large number of consultants capable of quickly producing complex deliverables. Now, scarcity is shifting.

What becomes difficult to reproduce is no longer raw production. It is the ability to ask the right questions, strategic arbitration, human reading of organizations, decision-making responsibility, and political change management.

In other words, senior judgment. This evolution could explain why several firms are already reorganizing their internal structures around profiles more oriented toward: client relationships, organizational transformation, AI governance, or supervision of intelligent agents. The classic pyramid could gradually give way to much flatter structures.

Toward the Augmented Consultant

However, the story does not simply amount to massive destruction of junior positions. Some companies are adopting the opposite approach: using AI to accelerate the skill development of young recruits.

At IBM, several executives recently explained that AI agents enable junior profiles to produce deliverables much more quickly that were once reserved for more experienced consultants.

The emerging idea is therefore not necessarily the disappearance of juniors, but their transformation. Tomorrow’s consultant could become an “augmented architect” from their early years: piloting AI agents, critical validation of results, orchestration of hybrid workflows, supervision of generative models, strategic interaction with clients. This logic profoundly changes the very definition of professional learning.

A Systemic Risk for Organizations

The question extends beyond the consulting sector alone.

All knowledge industries rely on similar mechanisms: law, finance, audit, marketing, engineering, research, media. In each of these domains, the tasks historically assigned to juniors are precisely those that AI automates most rapidly.

Yet these tasks also constituted the training foundation for future experts. The risk is therefore generational. If companies massively reduce their junior recruitment in the short term to gain productivity, they could create a massive deficit of experienced skills in the medium term.

This tension is already beginning to appear in several technology sectors.

AI Is Changing the Nature of Cognitive Work

What is happening today is not merely technological substitution. It is a redefinition of the intellectual value chain. For decades, scarcity resided in access to information and analytical production capacity. Generative AI makes these resources much more accessible.

The new scarcity then becomes: discernment, contextualization, critical thinking, responsibility, the ability to make decisions under uncertainty. In this context, the companies that will survive will probably not be those that eliminate their juniors the fastest. They will be those capable of reinventing their training around intelligent collaboration between humans and AI agents.

The central question is therefore perhaps not: “How many jobs will AI eliminate?” but rather: “How do we train humans capable of supervising the systems that will replace part of human work?”