The False AI Revolution. Mexico Risks Its Productive Sovereignty

Full credit to the original author, Víctor Jesús Hernández Salinas.

The original article puts forward an uncomfortable but necessary idea: in Mexico and Latin America, artificial intelligence has been celebrated first as spectacle and only later as a tool for real transformation. This perspective is especially relevant for interAlcaldes because it connects directly with a central challenge for local governments and municipal economies: technology alone does not transform reality if institutions, companies, and cities continue operating with disorganized data, limited capabilities, and weak execution cultures.

The debate is no longer about whether AI can generate text, images, or conversational assistants. The real question is whether Mexico can turn this wave into productivity, investment, and geoeconomic advantage within its relationship with the United States and its broader network of trade partners across Europe and Asia. The International Monetary Fund projects Mexico’s growth at around 1.5% for 2026, while the OECD highlights the country’s resilience but warns that accelerating digitalization and upgrading workforce skills will be critical to boosting productivity and living standards.

This is precisely where the author’s thesis gains strength. The generative AI boom democratized access, but it did not solve the underlying productivity problem. Mexico needs less fascination with interfaces and more capacity to integrate intelligent systems, automate processes, audit decisions, and translate data into measurable outcomes. This shift is especially important because the United States remains Mexico’s main economic anchor: bilateral trade in goods reached $872.8 billion in 2025, with U.S. exports to Mexico growing by 1.2% and imports from Mexico increasing by 5.8%. At the same time, nearly 80% of Mexico’s exports go to the U.S., while China, Germany, Japan, and South Korea remain key suppliers. This confirms that Mexico’s technological competitiveness is already being shaped within a global trade network spanning the Americas, Europe, and Asia.

Yet the biggest obstacle remains domestic. The original article rightly emphasizes that AI does not fix disorder—it exposes it. Official data makes this clear. In 2023, Mexico had 5.45 million economic units, 95.5% of which were microenterprises. While 86.2% of these businesses used the internet, only 25.3% had access to computer equipment—still an insufficient foundation for large-scale, advanced automation. Digitalization in Mexico is uneven, concentrated in specific sectors and regions, while much of the economic base remains constrained by small scale, informality, and limited technological capacity.

The OECD reinforces this diagnosis. Mexico lags behind several regional peers in AI adoption and ranked eighth in the Latin American AI Index in 2025, with weaknesses in infrastructure, data centers, high-performance computing, and enabling regulatory frameworks. In other words, Mexico may be a manufacturing powerhouse without yet being a powerhouse in applied intelligence. This gap matters for industrial municipalities, logistics hubs, and border cities that depend on nearshoring, because the next phase of competitiveness will not be determined solely by wages or location, but by data quality, cybersecurity, energy availability, talent, and decision-making speed.

The education front further supports Hernández Salinas’s concerns. A 2026 study by Tecnológico de Monterrey and the Digital Education Council found that AI usage among higher education students in Latin America increased from 86% to 92%, and among faculty from 61% to 79%. However, the same study reveals a deeper gap: 65% of students fear that AI may promote superficial learning, only 36% of professors actively teach how to use it, and overall AI literacy remains low, with average scores of 1.5 out of 4.0 among students and 1.6 out of 4.0 among faculty. Mexico is producing fast adopters, but not yet enough system architects, bias auditors, or automation designers with strong civic and industrial awareness.

From an international perspective, the risk is twofold. The World Bank has warned that AI can expand access to knowledge, open markets, and boost productivity, but it can also widen the gap between prepared and unprepared countries. Similarly, the IMF notes that for Latin America and the Caribbean, fully leveraging AI will depend on its diffusion across industries and the ability to facilitate labor and business transitions. This means Mexico cannot limit itself to consuming foreign platforms while negotiating trade with the United States, attracting manufacturing investment from Asia, and repositioning itself in Europe, South America, Africa, and Oceania. It must build its own capabilities in governance, infrastructure, localized models, and auditable ethical frameworks.

The central challenge going into 2026 is not choosing between modernity and stagnation, but between technological dependence and operational sovereignty. If Mexico turns AI into a territorial productivity policy, municipalities can deploy it in logistics, public safety, water management, citizen services, and investment attraction. If not, AI will remain just another imported layer of sophistication placed on top of fragile institutions. The next competitive advantage will not come from clever prompts, but from the ability to organize data, develop critical talent, and govern algorithms with a clear public vision.

What do you think? At interAlcaldes, we want to hear your perspective on how Mexico and its municipalities should navigate this technological turning point. Share your thoughts and join the conversation.

Article first published in: http://hersalvj.blogspot.com/2026/03/la-ilusion-de-la-inteligencia.html

Written by: Víctor Jesús Hernández Salinas

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