By Berend Booms | Associate Editor | Future of Assets

Over the past several years, artificial intelligence has steadily moved from the periphery of industrial operations into the center of how many organizations function. What started as experimentation around analytics and automation is increasingly becoming embedded into decision-making itself. In our world of asset management, systems now help determine when maintenance should happen, which risks deserve attention, how production schedules are optimized, and in some cases even which actions operators should take in real time. 

Much of this progress has been meaningful. In asset-intensive industries especially, AI carries enormous potential to improve safety, reliability, efficiency, and operational visibility. There are environments where faster analysis genuinely prevents harm, where predictive systems reduce unnecessary downtime, and where intelligent automation allows people to focus their attention on more valuable work. 

At the same time, something deeper is beginning to surface beneath the enthusiasm surrounding these technologies. As AI becomes more capable, questions are emerging that have less to do with technical feasibility and more to do with humanity itself. We are approaching a point where the question is no longer simply whether we can build these systems, but whether we fully understand what their growing influence means for human responsibility and judgment. With this shift come considerations on responsibility, accountability, ownership, dignity, and human judgment. These questions explore what happens when systems increasingly shape not only what we think we should do, but also how we think we should do it. 

This is what makes Pope Leo XIV’s newly released encyclical Magnifica Humanitas such a compelling contribution to the broader conversation around AI. While the document emerges from a religious institution, its core argument reaches far beyond theology. At its heart sits a remarkably human concern: how do we embrace increasingly powerful technologies without allowing them to diminish the very qualities that make us human in the first place? 

Beyond Intelligence: The Question of Human Judgment 

One of the more compelling aspects of the encyclical is that it does not approach AI from a purely technological perspective. Leo XIV frames artificial intelligence as part of a much larger societal transformation, comparable in scale to the Industrial Revolution of the nineteenth century that completely reshaped labor, economics, and society. The symbolism behind his choice is deliberate. The encyclical was signed exactly 135 years after Pope Leo XIII’s Rerum Novarum, the landmark text addressing the social consequences of industrialization.  

The parallel feels particularly relevant for asset management and industrial operations. Historically, industrial revolutions have not simply changed how work is performed; they have also changed how people relate to work itself, how authority is distributed, how decisions are made, and how responsibility is understood inside increasingly complex systems. AI introduces a similar tension. In many operational environments today, decision-making is becoming progressively abstracted. Operators and engineers increasingly interact with AI-powered recommendations generated by systems they may neither fully understand nor entirely trust. Models identify anomalies, prioritize work orders, optimize production flows, and forecast failure probabilities using layers of statistical reasoning that remain largely invisible to the people relying on them. Without the right levels of transparency, many will wonder when support starts to give way to substitution.  

For me, there is a big difference between a system helping a technician make a decision and that same system becoming the decision-maker itself. The distinction matters because responsibility becomes harder to trace once human judgment starts dissolving into algorithmic outputs. 

Leo XIV repeatedly returns to the idea that humanity cannot be reduced to optimization. In one passage, he warns against allowing people to become “mere instruments within an algorithmic order.” This really resonates with me, especially if we consider this in the context of industrial environments, where the pressure for efficiency can easily overshadow the less measurable dimensions of work. 

Anyone who has spent time around complex operations understands that good decision-making rarely emerges from data alone. Experienced operators often recognize subtle contextual signals that systems struggle to capture fully: the way a machine sounds, the smell it emits, the frequency at which it vibrates, or the speed with which it runs. Skilled technicians develop intuition through years of exposure to abnormal conditions, near misses, workarounds, and operational realities that never fully appear inside structured datasets. What this illustrates is that there remains a form of human judgment embedded within industrial work that is deeply relational and experiential. Losing that entirely would not constitute technological progress; it would represent a narrowing of how organizations understand ‘intelligence’ itself. 

Automation, Accountability, and the Distance Between Action and Consequence 

The encyclical also spends considerable time examining the concentration of technological power. Leo XIV warns about what he describes as an unprecedented form of “private technological power,” where a relatively small number of organizations possess levels of influence that increasingly rival those of governments themselves.  

That concern feels difficult to ignore when looking at the current trajectory of AI development. A growing share of critical systems, infrastructure, and decision-making capability now depends on technologies controlled by a relatively small number of companies. One only has to look at the current relationship between the United States Department of Defense and Anthropic to get a taste of what this dependency looks like. The Anthropic case demonstrates that dependency on AI is not merely a technical concern, but a structural vulnerability. When critical capabilities become concentrated inside private platforms, political conflict, contractual disagreement, or strategic divergence can quickly translate into operational instability. For industrial organizations, this raises a fundamental governance challenge: adopting AI at scale may increase efficiency and capability in the short term, while simultaneously deepening long-term dependence on opaque external vendors that can shape, restrict, or withdraw critical functionality.  

Besides introducing new forms of operational vulnerability, dependencies of this magnitude also introduce moral distance. The more abstract systems become, the easier it becomes for accountability to diffuse across layers of automation, vendors, data pipelines, and decision-support systems. At some point, failures, conflicts, or unintended consequences will emerge, and when this happens, responsibility becomes increasingly difficult to locate. 

The encyclical’s warnings around autonomous weapons systems illustrate this dynamic in particularly stark terms. Leo XIV argues that reducing human involvement in warfare lowers the threshold for conflict itself because decision-making becomes detached from direct human consequence.  

While industrial operations are obviously different from warfare, the underlying principle still applies. The further humans become removed from operational consequences, the greater the risk that ethical responsibility becomes diluted. 

In asset-intensive environments, this matters profoundly. We must not forget that these industries do not operate in abstraction. Their decisions shape worker safety, have direct environmental impact, provide public infrastructure, safeguard energy systems, keep transportation networks functioning, and by and large drive community resilience. AI may improve how decisions are executed, but it does not eliminate the moral weight behind those decisions. 

I have participated in many conversations around ‘human and AI convergence’ and the idea of ‘keeping humans in the loop,’ yet I often find those conversations incomplete. Aspirational language like this appears frequently in technology discussions without much clarity around what it actually requires in practice. Keeping ‘humans in the loop’ is not enough if those humans can no longer meaningfully understand, challenge, influence, or override the systems around them.  

Preserving Humanity in Asset Management 

I am particularly drawn to this conversation because of the deep connection asset management has to stewardship. To me, asset management is not simply about extracting maximum performance from your physical assets. It is about balancing long-term value, safety, reliability, sustainability, and responsibility across interconnected environments that affect people’s lives in tangible ways – now, and in the years to come, sometimes even beyond what we can experience within our lifetime. That’s the kind of balance that requires human judgment. It requires the ability to navigate trade-offs that cannot always be solved mathematically. It requires empathy for the people operating within those systems. It requires leaders willing to look beyond efficiency alone and ask broader questions about impact, resilience, and responsibility. 

AI can absolutely strengthen the way we work. Used thoughtfully, it can augment human capability in extraordinary ways. It can surface patterns humans would miss, reduce repetitive burdens, increase safety in hazardous environments, improve situational awareness, and support better operational outcomes.  

What the encyclical teaches us is that technological capability and human wisdom are not the same thing. The more advanced our systems become, the more intentional we may need to become about preserving the human qualities that cannot easily be automated away: reflection, accountability, moral judgment, craftsmanship, intuition, care, and the ability to see people as more than variables inside an optimization model.  

This, to me, is the central message behind Magnifica Humanitas: humanity is not an abstract philosophical idea we preserve passively, but something we practice continuously through responsibility, restraint, dialogue, and conscious decision-making.