AI automation threatens the employment of young graduates. However, it must instead accelerate the integration of juniors and the transformation of professions.
Faced with the rise of generative AI, the first reflex of companies was to automate execution tasks, directly threatening the employability of young graduates. However, depriving yourself of these profiles is a managerial error. AI must not exclude junior profiles, but become the accelerator of their integration and the transformation of professions.
In recent months, the press has relayed alarming figures on job prospects for new generations. Among the most commented statements, that of Dario Amodei, CEO of Anthropic, stood out: according to him, AI could eliminate up to half of junior office jobs in the next five years, with a risk of a sharp increase in unemployment in skilled professions. A deliberately alarmist prediction, but which says something about the current reflex of companies: entrusting AI models with the execution tasks which until now served as the first learning ground for young graduates. This threat also hangs over the ESN professions. For a year, the first managerial reflex has been to outsource simple and time-consuming tasks to LLMs. From meeting minutes to packaging computer code, the junior’s historical execution function seems to evaporate. Should we therefore acknowledge the sacrifice of the new generation? This would miss the true value of this technology. Just as the arrival of the internet 25 years ago aroused the same fears before creating new professions, AI must be understood not as a substitute, but as the most powerful lever for onboarding and augmented mentoring ever put in the hands of companies.
Augmented mentoring: AI as a personalized coach 24/7
The main obstacle to the integration of young graduates has always been the available time of experienced profiles. This is where the AI turns the tables by becoming a personalized tutor for the junior. It does not replace human experience, but it debugs, guides and structures the first missions.
This acceleration radically redefines the organization of work. Let’s take the example of computer maintenance activities. Until now, complex incidents were reserved for seniors. Today, by searching the history of documentation in record time, the AI summarizes the resolution of past failures and allows a junior to take charge of complex subjects from their first weeks. This time saving on learning allows the junior to skip the execution stages to concentrate, from the start, on missions with high added value.
The trap would obviously be to delegate everything to the machine and lose basic business skills. When an AI generates a PowerPoint presentation, the value now lies in the clarity of intent and rigor of reasoning, not the time spent on layout. The junior engineer must focus on his strengths after school, namely his academic knowledge and logic, to challenge the deliverable of the machine which remains a thinking partner.
Skill versus experience: the new junior-senior pair
Beyond technique, the integration of juniors is an opportunity for organizational engineering. Over the past year, the majority of companies have been making the same mistake: they are using AI to reproduce the past, simply automating existing, pre-cut processes.
This trend is already reflected in the workforce on a global scale. In France, just over a quarter of business leaders (26%) say that over the last year, junior positions have been reduced or eliminated due to the gains made with AI. If France displays one of the lowest rates after Japan (16%), the divide is spectacular elsewhere: China peaks at 61% reduction in entry-level jobs, closely followed by Australia (57%), India (50%), the United States (40%) and Germany and the United Kingdom (38% respectively)*.
To go further, the company sorely needs the perspective of this “native AI” generation. Less formatted by decades of ingrained habits, young graduates have a spontaneous agility to break the codes and shorten decision-making circuits.
According to an internal study, if 75% of employees use generative AI across all generations, the enthusiasm and natural curiosity of juniors make them unique drivers. They constantly test and explore the latest solutions and spontaneously share their discoveries. This dynamism fully justifies the choice to strengthen the transformation teams with recently graduated profiles. By creating intergenerational pairs, the company is implementing an unprecedented inversion of the transmission of knowledge where the junior brings his technological agility and his culture of promptness, while the senior guarantees the professional framework and perspective.
Towards the merger of professions
This collaboration accompanies the inevitable change leading to the merger of technical and functional profiles.
We are already seeing developers moving massively towards the functional translation of business needs, while functional consultants are now capable of implementing applications themselves without an intermediary. Juniors, armed with this dual hybrid skill facilitated by AI, will be the first architects of these new “two-in-one” professions.
The ecosystem’s first response was to remove juniors to achieve immediate productivity gains. This short-term calculation is dangerous, because AI does not replace skills renewal. In reality, this technology becomes the best ally for relieving seniors from repetitive tasks, finally freeing them up with the time needed to pass on their expertise to juniors, who will become the pillars of tomorrow’s company. The question is therefore not whether AI will replace young talents, but to realize that companies which integrate juniors to deploy this technology will gain a decisive head start over their competitors.
* Source: “AI weakens the employment of juniors in France”, Le Monde Informatique.
