“The role of data scientist didn't exist in 2013; in three years, it will be gone.”

Published : 16/07/2026

Will AI destroy or create jobs? For Marie-Ange Giuseppin and Jérôme Rave (partners at Inetum Consulting) the question is misguided. The real debate lies elsewhere.

The role of data scientist emerged in the early 2010s, when data scientist consultants began to appear, now we believe the decline has already begun. From this paradox, we draw insights into the jobs of the future that contrast with the prevailing debate.

A modern office setting where three individuals are positioned around a desk with computer screens displaying lines of code, one individual in the foreground gesturing while speaking as two others sit near the monitors and focus on the exchange, illustrating a collaborative work environment centered on technical or digital development tasks.

Let's be blunt: In your opinion, will AI destroy or create jobs?

Jérôme: It’s a debate that goes in circles and is framed the wrong way. The job of a data scientist didn’t exist in 2013, and in my opinion, in three years, it won’t exist anymore. The same goes for consultants: in the 1960s and ’70s, there were experts, and the consulting profession didn’t emerge until the 1980s. The real question isn’t whether things will change; it’s the speed at which the job market will evolve. As long as we approach the issue from the tired angle of job losses, we’ll miss the real point. The logic of trying to reduce a net loss doesn’t hold up. The question is more about how we redistribute the productivity gains within companies.

What kinds of candidates are you hiring today?

Marie-Ange: Candidates who can ask the right questions, rather than provide the right answers, because AI is becoming increasingly capable of doing that. We’re looking for “T-shaped” candidates: those with solid vertical expertise (in banking or law, for example) and a horizontal ability to interact with AI. The distinction between business and tech is gone: in the future, a marketing director will open a coding terminal just as they open Excel today.

We’ve long talked about “hard skills” and “soft skills”: the former can be learned, but empathy; if you don’t have it, is hard to acquire. Added to this are critical thinking (including creativity) and what I call “exoskills”: a consultant empowered by AI, much like an exoskeleton. “Hard” and “soft” skills, critical thinking, and exoskills: this is the profile of the employee in the age of AI.

If AI makes us better, why wouldn’t it just do our work for us?

Jérôme: Because there will always be a decision-making aspect that it can’t handle: AI executes; it doesn’t decide. Take two consultants, the same client, and the same instruction: “Read this request for proposals and draft a response for me.” You won’t get the same result, because each person configures the tool based on their own experience. We all operate within contexts that the machine lacks. A static context (our lived experience, our history) and a dynamic context (the situation at hand). No two people’s experiences are identical, and that’s where people make the difference.

What’s changing, then, isn’t that humans are disappearing—it’s that their value is shifting from the accumulation of knowledge to judgment. A criminal lawyer used to spend three days locked away in their office poring over case law, but tomorrow, AI will provide them with a summary of the 56 key decisions they need to keep in mind. They can devote that saved time to thinking about the substance of the case. AI automates a large part of their work, but they retain a critical eye, and it is always they who make the final decision. Yet to decide is to choose: to be able to explain what is being ruled out as well as what is being retained, in order to refine a line of argument in a courtroom case, for example. This is a matter of free will, and the machine does not possess it.

So, what are the jobs of the future?

Marie-Ange: The most traditional roles already exist. The operator, the prompt librarian, the AI ethics officer—a role that emerged from the rise of ethical concerns... Others are on the way: in the service sector, supply process managers, modeled after the supply chain in manufacturing; and, following the chief digital officers of the 2010s, digital AI officers tasked with coordinating all of a company’s agents. Take agriculture, for example: farmers no longer spread fertilizer themselves; drones handle it on a per-square-meter basis, depending on rainfall and soil fertility. We could call this profession “agridronomist.”

How can you prepare, whether you’re a company or a recent graduate?

Marie-Ange and Jérôme: For a recent graduate, you shouldn’t specialize in AI alone, nor in a single profession, but rather in a profession combined with AI. Otherwise, you’re banking on a skill whose value will decline. Companies also have a social responsibility: everyone should have access to AI, because lacking that access effectively puts a stop to people’s careers. For the past thirty years, the number of cashiers has been declining. Yet when a machine malfunctions, we’re very glad to be able to call on a cashier. In the future, we’ll automate even more, but we’ll always need a “super cashier”—someone capable of stepping in when things go wrong. That’s precisely what a machine won’t be able to do.

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