AI automates career entry tasks, and deeply modifies the skills rise trajectories. A change that calls for a strong response from higher education.
The articles listing the professions threatened by AI are multiplying. Just like those who, in mirror, praise its promises of productivity. But a dead angle remains: the place of juniors in this new work organization. Those who, again yesterday, learned from direct experience, find themselves today excluded from the basic missions, precisely those that artificial intelligence now performs more quickly, more proper.
In the financial sector, for example, automation is already well rooted. Big Fours launched their own agentic AI platforms. Deloitte and Ey bet on systems capable of collecting, reasoning, executing and recommending, as many functions formerly entrusted to junior analysts. In France, Crédit Agricole is experimenting with the Generative Search. Société Générale integrates AI into its risk management. Internationally, Bloomberg, Nyse and Amazon Bedrock redefine the performance standards in real time.
Is a world of white collars without juniors being born?
In many companies, the answer is yes, or at least, the trend is installed. Two thirds of Wall Street junior analysts could be replaced by AI. Why recruit a beginner, when a equipped senior can produce faster and without error? The economic argument is formidable.
But to look more closely, this logic hides a paradox. Many professionals today recognize that the “repetitive” tasks accomplished at the start of their career have been formatting. They forge reflexes, develop a rigor, and above all allow you to learn the implicit codes of the profession.
It is not only a technological issue. It is a strategic, educational … and societal challenge. The question exceeds businesses. It also concerns training institutions, still poorly prepared to offer concrete and effective alternatives. Debates often focus on the uses and authenticity of the work. Too often, discussions are reduced to a cat and mouse game: on the one hand, tools to detect the content generated by AI; on the other, students who bypass them.
However, the issue is elsewhere: how to train in the era of artificial intelligence without giving up learning by practice? How to maintain a progressive skills rise, while taking advantage of advanced digital tools?
Train in the AI era: reinvent the skills rise routes
It is not only a question of developing agility or critical thinking. What is missing today is a space where juniors can question the rules of the game, make decisions in real conditions, and understand what they really bring. In a world where execution tasks are supported by tools, new professionals must learn to interpret, arbitrate, assume choices.
This supposes more demanding learning situations: real data, professional tools, scenarios with several dimensions (economical, climatic, regulatory, etc.). The context does not come after learning. He is one of them. It is not a question of juxtaposing technological bricks and knowledge blocks, but rather of rethinking the joints between advanced tools, operational realities and systemic issues. It is not the technology that makes the transformation, it is the way it is integrated into paths that makes sense.
Deploying advanced education requires designing situations where students work on real cases, question their room for maneuver, explore tensions between efficiency, impact and feasibility. Each sequence becomes a situation to be resolved, built from well identified professional dilemmas.
Well integrated, AI becomes a strategic lever
Technological progress has never been incompatible with transmission. It acts as a catalyst, accelerating educational changes, forcing to clarify what is transmitted and why it is transmitted. In this universe, teachers’ expertise is more essential than ever. It is their ability to adapt, their discernment, their requirement and their sense of support that give its management to innovation. AI becomes their great power to form a lucid, built and capable of acting.
