Regulation, Competition, and Data Control in AI: Global Regimes and Latin American Implications

This article examines a pivotal, under-the-radar struggle shaping the future of artificial intelligence: who controls the data that trains AI systems and under what terms. It highlights regulatory efforts in the European Union to curb data practices of big tech, frame AI regulation as an issue of competition, and prevent entrenched monopolies from widening in the digital economy. The piece notes that AI has shifted from a distant promise to a daily infrastructure, reliant on vast data pools—texts, images, public and private records—to power generative models. It emphasizes concerns about concentration of power among a small set of firms that control models, compute, platforms, and data repositories, and it discusses how regulation in this space aims to balance protection of digital rights with maintaining healthy competition. While Europe leads with stringent data protection and AI governance, the article also surveys responses from the United States and China, pointing to a fragmented global landscape. For Mexico and Latin America, the piece argues, there are strategic implications: data regulation and fair access to AI benefits could determine national sovereignty in digital transformation. The article calls for learning from Europe’s regulatory experiments without copying them, proposing that regulation can be a tool for development and governance, especially in public administration and digital government. It concludes that the debate is ultimately about who writes the rules of the AI era and how governance structures will shape power dynamics in the century ahead.