IESE Insight
Leading with Magnificent Humanity in an automated world
Pope Leo XIV’s encyclical on AI holds applicable lessons for business, as highlighted at an IESE forum held before the Pope’s visit to Spain.
The growing power of AI forces us to confront three profound questions: our duty to the global poor; the need for moral imagination and ambition regarding human flourishing; and the need for discernment on the nature of AI models. This was stated when Pope Leo XIV released his first encyclical, Magnifica Humanitas, or Magnificent Humanity, in May 2026.
However, it may come as a surprise to discover that this clarion call was issued not by the Pope but rather by Chris Olah, cofounder of the AI giant Anthropic, who was at the Vatican when the Pope made his official presentation.
Also notable is that it was the first time in history that a Pope had presented an encyclical in person, and that he had chosen AI to be the subject of his first major teaching. Moreover, it was released on the 135th anniversary of Rerum Novarum, the encyclical of his namesake, Pope Leo XIII, written during the Industrial Revolution and likewise insisting on the preservation of human dignity in another time of radical change.
Ricardo Calleja, a lecturer in Business Ethics at IESE, and Javier Sanchez Cañizares, a researcher and theologian at the University of Navarra, discussed the headline-making encyclical during a Rafael Termes Forum held at IESE Madrid just prior to the Pope’s historic visit to Spain on June 6-12, 2026. Their conversation drew out several key points for business practitioners to bear in mind when incorporating AI into their decision-making and organizational processes.
Don’t assume intelligence or neutrality
Let’s start with the nature of the tool itself. As the encyclical states, artificial intelligence may “imitate certain functions of human intelligence,” even surpassing it in terms of speed and computational capacity, but it lacks a true understanding of what it processes. It does not know what matters or why. That depends entirely on human wisdom derived from life experience.
“Humans are the only ones capable of defining what does and doesn’t count, linked to some strategic purpose or end as defined by a person,” insists Sanchez. AI is incapable of doing this on its own.
This leads to the encyclical’s second key distinction: “We cannot consider AI to be morally neutral. In reality, every technical tool embodies choices and priorities through what it measures, ignores and optimizes, and how it classifies people and situations.”
As Sanchez reminds business leaders, all the data used to feed and train AI models are the product of a prior human filter who decided what was and wasn’t relevant or important. Those biases are baked in, so whenever using any AI tool, one is consciously or unconsciously assuming those predefined, biased viewpoints. He advises decision-makers to always question the underlying assumptions that informed the algorithm they are using.
Stay vigilant! Information is not the same as knowledge
The danger of ignoring this inherent bias is believing these tools are objective and failing to give them the careful consideration they deserve. Humans, too, have natural limitations, Sanchez admits, but “once aware, we can try to correct or compensate for them in some way. AI, in contrast, operates under a dictatorial logic: Anything that lies outside its algorithmic frame of reference simply does not exist.”
If leaders delegate their business decisions and strategies to an AI model that only recognizes what has been previously labeled, they run the risk of becoming blind to disruptive innovation, the unexpected or, even more serious, the human reality of their customers and employees.
To avoid this, leaders must appreciate that information is not the same as knowledge: finding statistical correlations at astonishing speed is not causality — explaining the why and not just the what. Don’t let AI become an “explanatory substitute,” cautions Sanchez. Instead, leaders must “use their own nose to smell when something seems off.”
Use your wisdom because humans learn differently
Calleja shares his own story of a classroom exercise where students were tasked with presenting various market analyses. Those who relied on AI for their results did worse than those who hadn’t used AI. Calleja attributes this to students blindly trusting AI-generated models without wrestling with the numbers for themselves. When the outcomes didn’t match their forecasts, they struggled to understand their own tools and recalibrate their decisions accordingly. There can be an irrational reliance on AI, Calleja observes.
Sanchez stresses that humans and AI have very different ways of learning. AI uses “a form of statistical adaptation based on data and feedback,” in the words of the encyclical. Human beings, on the other hand, “grow over time through choices, mistakes, forgiveness and fidelity.”
For Sanchez, this is one of his favorite parts of the encyclical, because it highlights precisely those features that can never be embodied by a machine: our empathy, “whether in the vulnerability of a sick person or in the face of a stranger,” he says.
The encyclical puts it this way: “So-called artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships and do not know from within what love, work, friendship or responsibility mean ... for they lack the affective, relational and spiritual perspective through which human beings grow in wisdom.”
“If you delegate to a machine what only you can do,” warns Sanchez, “you aren’t gaining efficiency; you’re losing the ability to see.”
Moral judgment cannot be delegated to algorithms
Delegating ethical responsibility to a machine is what Sanchez calls “a dereliction of duty.” Moral judgments cannot be reduced to optimization calculations.
“Indeed, entrusting an algorithm in practice with the power to select who is worthy or not, without anyone bearing responsibility for that judgment, is to hand over the task of redefining the boundaries of human possibilities,” states the encyclical.
Sanchez uses the illustration of AI acting as a judge in legal cases. The AI judge may be able to process case law and deliver a verdict faster than any human judge could, yet as a society we would still demand the right to a human explanation of the reasoning behind the verdict. “We would not accept a guilty verdict based merely on data correlations,” says Sanchez.
Sanchez extends this analogy to business: When you deny someone a promotion or reject a loan application, the affected person has the right to have a human reason for that decision. Failure to do so undermines trust, which no amount of efficiency can replace.
Make time for reflection
AI’s impressive speed and constant information generation can have the unfortunate effect of dumbing us down, until we lose our critical thinking ability: “It becomes difficult to grasp reality as a whole, to ask profound questions about meaning, or to develop authentic, critical and creative thought. Many already report signs of dehumanization, where people may ‘know many things’ but struggle to find direction in their lives, partly due to an inability to connect information with deeper knowledge or maintain a sense of purpose,” states the encyclical.
As an antidote, the encyclical urges a return to “the essential exercise of research, reflection and discernment.” Leaders must preserve spaces “that incorporate silence, in-depth study, reading and judicious analysis.” Besides guarding this in our own lives, educational systems must also preserve this as core.
Constant optimization is not always ideal for human performance, says Sanchez. Wisdom is knowing when to stop. If success is measured only in terms of speed or cost savings, then we risk losing exquisitely human dimensions like empathy, relationships and maturity. We are basically letting decisions be made without a person signing off on them. And that would be a mistake.
The risk of regression and a call for prophetic leadership
The greatest risk is what the encyclical calls an “anthropological regression,” a hollowing out of the workforce, where technical progress is accompanied by a degradation in the meaning of work.
“Work remains a fundamental dimension of the human experience, for not only is it a means of sustenance, but it is also a context for expression, relationships and contributing to the community. Therefore, the problems related to work extend beyond the income necessary for family survival. A society that guarantees employment to only a small fraction of the population, despite having a high level of technical development, risks exposing many to forced inactivity, a lack of responsibility and the absence of daily tasks and stimuli, resulting in human and cultural impoverishment,” states the encyclical.
The Pope issued a stark warning, saying that, if left unchecked, AI could end up like the biblical Tower of Babel, destroyed by its own hubris. He pointed instead to the historical figure of Nehemiah, who patiently rebuilt Jerusalem in the 5th century B.C. Sanchez calls upon modern leaders to be like Nehemiah, someone who heard people’s cries and enlisted their help in the painstaking work of constructing a new and better reality.
This is the prophetic leadership that the age of AI demands: uniting people in your company, organization or institution to “rebuild what has collapsed and protect what is threatened,” to make AI more fitting for people’s dignity and worth.
“It is this intertwining of just institutions, credible witnesses and daily fidelity that sustains hope and provides clear direction for technological progress without allowing the heart to regress,” states the encyclical.
Business leaders must gauge their success not by how well they have managed to automate but by how well they have managed to balance the tensions between technology and the person, ensuring that efficiency gains also bring greater human growth and enlightenment. In short, it’s about building organizations that are both technically excellent and magnificently human.
This article is included in IESE Business School Insight online magazine No. 173 (Sept.-Dec. 2026).
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