Viewing artificial intelligence (AI) through the lens of capital requires a significant shift from conventional technological perspectives. It moves beyond the comfort of functional readings (AI as a tool optimizing processes) to place it within the denser terrain of structural mediations that reorganize social, economic, cultural, and symbolic life.
AI does not emerge as a neutral object but as an algorithmic infrastructure that redistributes access to knowledge, decision-making power, public visibility, and ultimately, meaning.
Conceptual Framework: Pierre Bourdieu’s Capitals
The conceptual framework of French sociologist Pierre Bourdieu proves particularly fruitful, not as a closed scheme but as a critical device. Economic, cultural, social, and symbolic capitals help understand how power is produced, circulated, and legitimized. AI reconfigures these capitals, accelerating, concentrating, or eroding them, and in doing so, it subtly rewrites the rules of the social game.
Contemporary extensions include cognitive capital, relational capital, articulatory capital, and ethico-reflexive capital. AI does not create these categories but intensifies and makes them visible.
Cognitive Capital: Expanded Memory and Its Gaps
AI undoubtedly contributes most evidently to cognitive capital. Systems capable of processing billions of parameters, trained on corpora including scientific texts, medical data, cultural archives, and global communication flows, form an expanded memory of civilization.
However, this cognitive capital is not homogeneous or democratic by itself. Its appropriation depends on three structural conditions: technological access, critical digital literacy, and institutional capacity to integrate AI into decision-making processes. The gap is no longer just between the connected and disconnected but between those who can critically engage with intelligent systems and those confined to consuming answers without understanding their assumptions.
Economic Capital: Productivity, Concentration, and Dependence
On the economic front, AI has become one of the primary drivers of global productivity. According to McKinsey’s study, “The Economic Potential of Generative AI,” AI could contribute between 2.6 and 4.4 trillion dollars annually to the global economy, particularly in healthcare, manufacturing, education, and financial services.
However, this economic capital is highly concentrated. Over 70% of global AI investment is in the US and China, while Latin America represents less than 3% according to the 2024 Stanford AI Index. The challenge is not whether AI generates wealth, but who captures it, where the value remains, and under what conditions it is integrated into local ecosystems.
Social Capital: Algorithmic Relationality
Traditionally, social capital has been understood as the collection of networks, relationships, and connections that enable subjects to mobilize resources. At first glance, AI seems excluded from this capital due to its lack of social life and affectivity. However, this reading is insufficient.
Embedded in platforms, recommendation systems, and everyday interaction environments, AI operates as relational infrastructure: it orders visibility, ranks attention, and modulates community formation.
Cultural and Artistic Capital: Preservation, Recombination, and Standardization
In the cultural domain, AI displays a profound ambivalence. It allows preserving and translating cultural heritage, indigenous languages, and historical archives. UNESCO and Google Arts & Culture projects have shown that AI can be an ally in preserving heritage, facilitating access to millions of digital cultural pieces.
However, there’s a risk of symbolic homogenization. AI models learn from dominant data, potentially reinforcing hegemonic aesthetics and central narratives, marginalizing local or peripheral expressions.
Symbolic and Ethical Capital: Contested Trust
Symbolic capital (trust, legitimacy, recognition) is among the most fragile in the algorithmic era. Edelman Trust Barometer surveys show that only 52% of people trust technology companies to develop AI ethically, and less than 45% trust governments to regulate it appropriately.
This erosion of trust indicates that AI is not merely a technical problem but deeply political and moral.
Here emerges ethical capital as a structural condition: algorithmic transparency, explainability, accountability, and respect for human dignity. These are not accessory values but requirements to prevent AI from fracturing social fabric.
Spiritual and Reflexive Capital: The Interrogation of Meaning
Although AI lacks spirituality, it indirectly impacts the spiritual and reflexive capitals of societies. By simulating conversation, creativity, and emotional companionship, AI confronts subjects with fundamental questions: what makes us human, where does meaning reside, and what is the value of embodied experience versus simulation?
America Latina and Mexico: Appropriation with Purpose
In Latin America, challenges intensify. According to CEPAL, over 40% of the region’s population lacks advanced digital skills, limiting their access to AI-generated cognitive capital.
In Mexico, while technological adoption advances, significant gaps remain between regions, educational sectors, and socioeconomic levels.
Maximizing AI’s multiple capitals requires an integrated strategy: sustained investment in education and critical digital literacy; collaboration between university, state, and productive sectors; local capacity development in research and technology design; and an ethical vision placing people and communities at the center.
AI is not merely another tool in the contemporary technological inventory. It’s a structural mediation that redistributes capitals, redefines divides, and reconfigures the horizons of possibilities for societies. Understanding AI through a multiple capitals logic avoids simplistic views and responsibly embraces the challenge of critically inhabiting this new algorithmic ecosystem.
The decisive question is not what AI can do for us but the kind of society we are willing to build and protect with it.
