Leonardo Medrano, Secretary General of Academia y Desarrollo at Universidad Siglo 21, says artificial intelligence can bring real educational benefits—but only if schools resist utopian cheerleading and reflexive rejection of the technology.
In a column published by LA NACION on October 5, 2026, Medrano lays out the central challenge: AI has moved into classrooms faster than meaningful policy debate can keep up. Two weak positions dominate. Some believe technology will solve education’s fundamental problems; others want to limit or ban it entirely. Neither gets to the core question: what should schools amplify, what should they restrict, and what do students need to learn in an AI-shaped world?
Three Real Advantages
Personalization makes the strongest case. Traditional education, Medrano observes, widened access to knowledge but relied on standardized models: the same content, pace, and teaching methods for students with vastly different prior knowledge, learning difficulties, interests, and speeds. AI can unsettle that one-size-fits-all logic. A student struggling with a concept can get more explanations and simpler steps, while a faster learner can take on deeper challenges. The system adapts to students.
Predictive capability is a second strength. Student interactions with educational platforms produce ongoing data on participation, performance, study time, completed activities, and delayed work. When schools use this information properly, they can spot learning difficulties early and intervene in time. They see who’s struggling before failure takes hold.
Active learning is the third advantage. Instead of passively receiving instruction, students can ask for another explanation when they’re confused, generate simulations, practice different scenarios, get immediate feedback, and choose to raise the difficulty. AI can become a tool for student-led exploration, not passive consumption.
The Genuine Risks
Mediano names three real concerns that call for institutional attention. First: misinformation. AI systems can produce plausible answers that are completely false. A fabricated answer can look just like a correct one. Students can't take information verification, source evaluation, and bias detection for granted; schools need to teach these skills directly.
Second: cognitive dependency. Less mental effort can weaken cognitive capacity. The key distinction is whether students use AI to strengthen their thinking or replace it. Schools need to preserve the struggle that builds capability.
Third: dehumanization. Technology can answer questions around the clock, provide endless exercises, and offer varied explanations. But education isn't just about answering questions. Medrano says AI should handle routine cognitive work efficiently, freeing human educators to mentor, challenge, inspire, listen, and build community. That’s the real institutional trade-off schools face.
What Students Actually Need
As access to information becomes trivial, Medrano argues, education’s value shifts from accumulation to application. Curricula should focus on three competencies: communication, creativity, and critical thinking. People will still need to explain ideas, build consensus, ask meaningful questions, understand different perspectives, lead teams, and create shared purpose.
Creativity matters more as AI produces technically correct answers quickly. The human edge lies in asking questions no one has answered, joining ideas that had been kept apart, imagining alternatives, and creating new solutions.
Mediano says education’s future isn’t about accommodating technological change; it’s about directing it. The question isn’t whether AI belongs in classrooms. It’s whether schools will use AI to expand people’s capacity to learn, create, understand, and transform reality—or drift into deployment without intention.
Why This Matters:
Schools face a plain economic and institutional reality: AI integration is happening, and passivity isn’t a strategy. Institutions that don’t set clear frameworks to distinguish beneficial uses from risky ones could squander real advantages while enabling real harms. Medrano’s approach rejects both naive techno-optimism and reactive restriction. It puts responsibility where it belongs: with educators and administrators, who must decide what problems AI can solve efficiently and what capacities students need to build on their own. That distinction between deploying tools and developing abilities reflects sound governance: using available resources well while protecting irreplaceable human functions. Schools that follow this approach keep control of their mission instead of drifting with technological momentum.