As generative AI sweeps through businesses, the CNAM’s Management Transformation Observatory offers its vision of the manager who will thrive in this new context: the minimalist manager ([FR]Make way for the “minimalist manager” in the age of generative AI). They know how to deal with complexity, information overload, and uncertainty by focusing on the essentials, making intelligent use of generative AI, and protecting themselves from overwork.
Inspired by Greg McKeown’s essentialism, the minimalist manager does not seek to do everything or control everything, but selects their actions based on their real impact. They apply the Pareto principle (20/80), prioritize their tasks, use AI to automate non-strategic tasks, and specialize in a few areas of expertise rather than remaining a generalist.
This approach requires discipline because it goes against the natural tendency to multitask, but it allows managers to create more value, orchestrate collective action, and support their teams in the gradual integration of AI.
While I find the idea relevant overall, some points leave me skeptical, or even seem to run counter to trends that aim to break us out of certain HR and managerial ruts that businesses have been stuck in for a long time.
In short:
- Minimalist managers focus on the essentials, use generative AI wisely, and protect themselves from overload.
- Technical specialization does not guarantee managerial competence, good managers structure collective action.
- Limiting oneself to generative AI is reductive, all forms of AI available must be mobilized.
- Managerial minimalism requires a systemic transformation of organizations.
- AI must reinforce the human element, and managers must ensure its balanced and respectful use.
Managers who rely on generative AI are one-legged managers
That wasn’t what struck me at first, but I couldn’t ignore the focus on generative AI. Yes, its impact is certain, and if we’re talking about AI today, even though it’s an old technology that’s already been used successfully in many fields, it’s because generative AI, with its use cases that are easy for anyone to understand in everyday life, is the figurehead that has turned a technical subject into a social issue.
But there is more to life than generative AI, far from it (AI for dummies who want to see a little more clearly), and by focusing solely on it, we risk missing out on many other use cases. Managers need multiple forms of AI for different needs, and the prevailing myopia that systematically brings us back to generative AI is becoming annoying and could cause us to miss out on many valuable opportunities.
Technical expertise ? managerial skills
This is the point that really struck me: “Today, this generalist approach is giving way to a return to expertise.”
We know it, we repeat it, and we have been complaining about it for years, in the business world and elsewhere (Reinventing the Leader Selection Process): promoting technical skills has never been enough to make good managers. In fact, the opposite is true: promoting experts to management positions without preparing them for their real mission—which is to create a framework for collective success, to help others grow, and to orchestrate without doing the work themselves—is doomed to failure.
Having encountered this frequently, I can say that “expert managers” are more often than not walking disasters. I refer you to this excellent post by Olivier Zara if you are looking for confirmation ([FR]Manager acting as a manager… or as an expert).
“The qualities needed to become a good expert are almost the opposite of those required to become a good manager.
To make matters worse, organizations don’t want to lose the expertise of the people they appoint as managers. So they are asked to be both experts and managers.”
I would add that when they are not asked, we often end up with a bad manager and lose a good expert in the field.
And I would even add that, precisely at a time when AI is set to become increasingly important in operations, managers will be asked to become… managers (With AI, the end of “doers”).
Contrary to what I read here and there, it is precisely because our world is becoming increasingly technological that “soft skills” or “non-technical skills” will become at least as important as “hard skills” for success (Let’s stop calling them ‘soft skills.’ They’re the hardest ones to master), either because your job will be based on human skills or because they will be essential for you to enhance your technical skills.
I understand that minimalist managers apply the Pareto principle and prioritize their tasks according to their impact, but I can see the risk of accentuating a well-known problem with managers who are trapped in operations because they excel technically but are incapable of building an autonomous and high-performing team.
Being a “minimalist manager” should not mean being a “super specialist” who does better than others. Rather, it should mean being a kind of strategist of simplicity: someone who chooses where to focus collective efforts, who sets a clear direction, who structures action around solid priorities, and who makes good use of AI to unleash the initiative and creativity of their teams.
Don’t get me wrong: of course a manager needs to understand what is going on, what people are doing and how, in order to constantly improve the organization of work, remove irritants, etc. (Managers are responsible for everything that goes wrong). But there is a big difference between understanding and being an expert.
Individual change will not be enough: transformation must be systemic
Secondly, I think it is simplistic to present this stance as a mere individual evolution.
No manager can sustainably apply effective minimalism in an organization that continues to value hyperactivity and dispersion and takes pleasure in constantly complicating things (
The organizational complication: the #1 irritant of the employee experience and How to Manage Complexity without Getting Complicated)
It is not enough to tell managers to be minimalist: the system in which they operate must also be transformed, because when things go wrong, it is usually due to the system rather than the people (The Problem Isn’t the Employee, It’s theSystem).
This requires a fundamental review of expectations, performance metrics, and ways of working together.
AI and humanism: what is the right balance?
Finally, I believe it is essential to maintain a humanistic vision of AI adoption. When used properly, AI can effectively relieve managers of many tedious tasks. However, it must never become a way of dehumanizing workplace relationships. The minimalist manager should be the guardian of this balance: using AI to enhance the human element, not dilute it.
Bottom line
The concept of the “minimalist manager” is a serious and useful one. But for it to be credible and have an impact, it needs to be clarified:
It’s not about becoming a better specialist, but a better conductor.
It’s not just an individual posture, but a systemic transformation.
It is not about reducing people, but about liberating them.
True managerial minimalism serves value, collective impact, and the creation of meaning, provided that the target is not mistaken.
Illustration: generated by AI via ChatGPT.
Related articles:
The future of work will be designed for humans
No one should be promoted to manager if they don’t know how to use ChatGPT
Augmented governance: AI as a lever for collective lucidity
ROI Vs. RONI: why businesses should invest in AI despite uncertain ROI
AI in the workplace: avoiding the Wall-E effect
AI in the digital workplace: a brilliant assistant, but an unreliable colleague
