AI doesn’t just change tools: it redefines roles

Artificial intelligence is often presented as an optimization technology. Automating CV sorting, generating marketing content, pre-qualifying leads: these are just some of the use cases already deployed in companies.

But behind these optimizations lies a deeper reality: AI isn’t just transforming tools, it’s changing the way roles are defined.

• Each automation raises questions about the real added value of human resources.
  – Each optimization highlights unclear or redundant missions.

AI doesn’t take work away, it just reveals that some jobs aren’t built around their true purpose.

Behind automation: the question of human added value

For a salesperson, recruiter or analyst, AI doesn’t replace the function, but it does force us to ask ourselves:

• what is my real contribution?

• what part of my role can’t be replaced by an algorithm?

As one executive summed it up:

“We need to focus on creating value, not cutting costs.

In this sense, AI refocuses the focus on what humans alone can provide: creativity, arbitration, meaning, inspiration.

New managerial expectations in the age of AI

As tools evolve, so do management practices.

• Management based on control and reporting is becoming obsolete.

• Leaders are now expected to do what AI cannot: think, frame and arbitrate.

The manager becomes the architect of meaning: he creates a framework, defines a direction, arbitrates priorities.

The specialists interviewed insist: AI must not be delegated to an isolated expert. All too often, AI projects are entrusted to brilliant technicians who are out of touch with business and cultural issues. The result: no overall impact.

Conversely, executives who explore AI for themselves, who test, who are amazed, discover real opportunities for transformation.

Training in AI skills: beyond generic training courses

In the face of these upheavals, generic AI training is not enough.

Learning how to use ChatGPT or Midjourney is useful, but not enough. Companies now expect :

• an understanding of business use cases,

• the ability to identify technical biases and limitations,

• a strategic and human reading of the impact of AI.

Knowing when not to use AI becomes a key skill.

One expert summed it up:

“General training is useful for understanding the language of AI, but it must lead to specialization by use case and purpose”.

The 10-20-70 model: putting people at the heart of AI success

According to the model popularized by BCG:

• 10% of investments should be in algorithms,

• 20% data and technology quality,

• 70% human skills, processes and cultural transformation.

The crux of the matter is not technical performance, but the ability to develop human talent capable of integrating AI into strategic vision.

Conclusion: management reinvented by AI

Artificial intelligence is not just a tool. It acts as a revealer:

• it exposes the flaws in existing roles,

• it forces managers to redefine their posture,

• it requires targeted, pragmatic skills upgrading.

AI doesn’t reduce the need for people, it makes it even more crucial. Provided managers are willing to reinvent themselves.