We read Magnifica humanitas, the text that Leo The Pope poses it on the scale of the person and the world. We pose it to that of leaders, or of those who are preparing to become one.
Let’s get rid of a misunderstanding right away. This encyclical is not about leadership, and we do not read it as a spiritual compass. What attracts attention is rarer: a voice far removed from business management reaches the same dividing lines as recent research on organizational leadership. We noted four of these convergences.
The machine manages, the human directs
AI can today carry out a growing part of executive work, that which is the most structured, the most procedural. Much less automatable is what requires judgment, social intelligence and an embodied presence: inspiring collaborators, arbitrating complex decisions, giving meaning, generating collective commitment. However, sensitive decisions, writes Leo XIV, risk being entirely delegated to systems that know neither empathy nor “the hope that people are capable of changing” (§102).
The AI does not know “from the inside what love, work, friendship or responsibility mean” (§99). This ability to evolve one’s leadership style and behavior is at the heart of executive training. Leadership development is not about optimizing potential, but about supporting individuals who are likely to question themselves and evolve.
Our experience of executive training turns an old illusion on its head: you do not become a leader by receiving knowledge, but by experimenting, by making mistakes, by starting again, accompanied by your peers. Theoretical reading is enlightening, but without practice, it is not enough. This is today one of the best-established lessons from research on manager learning, summarized by Herminia Ibarra’s formula: we act to think differently, rather than we think to act.
A shortcut that is a decoy
Leo XIV contrasts, in similar terms, the way in which an AI “learns” and the way in which a person is trained. The machine proceeds by “statistical adaptation” and involves “no inner growth”; on the other hand, the person allows himself to be “shaped by life” and grows “through his choices, his errors (…) and fidelity” (§99). Leo XIV concludes: “For an algorithm, an error is something to be corrected; for a person, it can be the beginning of a profound change” (§128). We know that managers and entrepreneurs often grow after failure. It’s the difference between describing someone’s qualities and faults, and looking them in the eye to help them become better.
AI excels at producing immediate gratification: personalized and rapid reading, an obsession specific to our time. But the feeling of having understood, if it is not followed by a change in behavior, dissipates quickly. This shortcut in the path to knowledge is an illusion because simplicity does not replace doubt, questioning and exchange, which are necessarily slow and uncertain.
Ease of access to answers, the encyclical warns, “accustoms us to delegating too much and seeking immediate answers, weakening our personal judgment and creativity” (§100). The speed with which we obtain answers “risks extinguishing the desire to ask questions, which only bears fruit with time” (§140). Training a person is slow work. Confusing the speed of understanding with the slowness of maturation is a major trap set by AI.
Know how to slow down, know how to refuse
Our conviction is that the responsibility of leaders is no longer simply to manage change but to govern its pace: knowing when to accelerate, when to slow down, when to welcome a request, when to refuse it. Our research on the leadership of conductors has shown this: the discipline of the collective allows the conductor not to direct constantly, but to identify the rare moments when it is necessary to intervene, with parsimony.
The encyclical also addresses this subject and calls for “slowing down where everything is speeding up” (§107). She defines AI education as the art of learning “to decide when and why not to use it” (§140). As AI frees up time, the temptation will be to intervene more. Sometimes the right thing to do is to slow down. It needs to be worked on. In our programs, a manager tests behaviors and practices that do not come naturally to him, compares his way of leading with peers from other sectors, then leaves with experiments to carry out with his team. None of these steps can be automated.
These connections do not make the encyclical a manual, but indicate that, on the question of what AI leaves to humans, worlds that do not speak to each other very well arrive at the same answer: judgment, relationships, ethics, social and environmental responsibility, the capacity to transform are not delegated to the machine. For those who lead, or learn to do so, it is less of a revelation than an essential reminder.
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