Mexican Universities Are Using AI Faster Than They Can Govern It
More than 60% of students and professors in Mexican higher education now use generative AI in their daily work. A national survey of 1.5 million students and 166,000 teachers-the broadest of its kind globally-shows the technology is not arriving on campus. It has already arrived.
The adoption rate is not marginal. Ninety-three percent of students and 95% of teachers know about generative AI. Sixty-nine percent of students and 73% of teachers say these tools have improved their academic performance. Eight out of ten students use systems like ChatGPT or Gemini to generate academic texts.
But the most consequential finding may be less obvious. Seventy-nine percent of teachers and 82% of students say generative AI is useful for complex cognitive work: reasoning, reflection, imagination, and creativity. Universities in Mexico are treating these systems not just as productivity aids, but as participants in thought itself.
Rules and Training Lag Behind Use
The problem is not adoption. It is governance.
Despite widespread use, self-perceived mastery of the technology averages 5 on a 10-point scale. Ninety-one percent of teachers and 76.2% of students say they need training. Seventy-six point seven percent of teachers and 67.2% of students in public institutions say they do not know their institution's rules for using these tools.
Mexico's universities have embraced AI faster than they have learned to govern it. When institutions lack clear rules and teacher training, convenience begins to shape the learning environment before anyone has defined what students should actually learn.
Mario Delgado, head of Mexico's Secretariat of Public Education, frames the challenge plainly: the discussion should focus not on permitting or prohibiting these technologies, but on defining their pedagogical uses, setting clear rules, and delimiting their scope.
Carlos Iván Moreno Arellano put it more sharply: "At this moment, we are failing." Current teaching and evaluation models may no longer fit a world where generative AI advances faster than norms, policy, and regulations can follow.
When AI Becomes Emotional Support
One detail in the survey signals a deeper shift. Nearly 92,000 students and just under 6,000 teachers use these systems for emotional support-to manage anxiety or simply to vent.
This changes what the conversation is about. A student turning to AI for comfort is not just seeking a faster answer. That student may be seeking patience, availability, or relief in an environment where institutional support feels thin. The question for Mexican universities is not only whether these systems can help students perform, but whether institutions are prepared for what happens when performance, thought, and emotional dependence begin to blur.
What Mexico's Universities Need to Do
The Secretariat of Public Education has proposed ten principles for AI use in higher education: recognizing generative AI as an established academic tool, establishing institutional guidelines, training teachers, updating curricula, rethinking assessment, building student literacy in these systems, closing access and governance gaps, incorporating gender perspectives, addressing student well-being, and strengthening humanities and social sciences across university formation.
That last point may matter most. Andrés Morales, UNESCO's representative in Mexico, said the debate over generative AI is ethical, philosophical, human rights-based, and pedagogical. Digital transformation only makes sense if technology serves humanity, not the other way around.
The real issue is not whether Mexico will use AI in higher education. It already does. The question is whether universities will teach students to command the tool without surrendering the work of judgment, doubt, and thought that a university is supposed to protect. That negotiation is already happening in Mexican classrooms. Whether institutions can move quickly enough to guide it remains open.
For educators navigating this shift, understanding both generative AI and LLM capabilities and frameworks for responsible adoption is essential. Resources on AI for Education can help institutions develop coherent strategies rather than reactive policies.
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