AI era forces academe to revisit how to teach critical thinking

By Arjay L. Balinbin, Associate Editor

MADRID — Artificial intelligence (AI) is forcing universities to confront a fundamental question: how do they teach students to think critically when machines can increasingly perform many of the tasks once used to develop those skills?

For Rafif Srour, dean of programs at IE School of Science & Technology in Madrid, Spain, the answer is not to resist AI, but to ensure that universities do not abandon the cognitive exercises that help students build analytical judgment, problem-solving skills, and independent thinking.

“The biggest mistake that can ever be made is to think that this tool can and should be used everywhere at the same time,” Ms. Srour said in an interview with BusinessWorld on June 2 on the sidelines of South Summit Madrid 2026, co-organized by IE University.

Universities around the world are racing to integrate generative AI into classrooms, research, and administrative functions. While the technology can improve productivity and learning outcomes, she warned that overreliance on AI could deprive students of opportunities to develop essential intellectual skills.

One example is summarizing academic papers.

For generations, students and researchers spent hours reading studies, identifying key information, and synthesizing insights into concise summaries. Today, large language models can perform the same task in seconds.

Ms. Srour said the concern is not whether AI can produce the outcome, but whether students still undergo the mental process required to arrive at it.

“Summary is not about the outcome,” she said. “It’s about the cognitive skills and the muscle that you build when you’re doing this.”

The exercise teaches students how to distinguish important information from noise, evaluate sources, and communicate ideas clearly, she said.

“If a generation never learns how to make a summary in their life, what do you think the impact would be on their cognitive development? Tremendous.”

The challenge extends beyond writing and research.

Ms. Srour said AI has become increasingly capable of performing analytical tasks that were once considered core components of university training.

Programs such as data science traditionally teach students how to identify patterns, interpret data, and support decision-making. Today, many of those functions can be executed by advanced AI systems within seconds.

The development does not make university education obsolete, she said. Instead, it requires institutions to rethink how they teach and what skills they prioritize.

“We should take from traditional education the depth, the technical core, the foundation,” Ms. Srour said. “But you should start adding different layers on top of this traditional education to prepare the students for the future of work.”

The schools most likely to succeed will be those that update their curricula while preserving the intellectual rigor that higher education has traditionally provided, she said.

Meanwhile, educational institutions that fail to evolve risk losing relevance.

“If you keep on resisting this and keep on teaching the same way that you’ve been teaching for the past 20, 50, or 100 years, what kind of minds are you developing?” Ms. Srour said.

The rapid pace of AI development is creating challenges not only for universities but also for governments and regulatory institutions, she added.

“For the first time, it’s changing at a rate that is much faster than our ability to cope as a society,” Ms. Srour said.

She said educational systems, legal frameworks, and public institutions are all struggling to keep pace with technological change.

For emerging economies such as the Philippines, broad technology literacy should become a national priority, Ms. Srour said.

“If I had a role to play, I would make technology literacy mandatory.”

Beyond AI literacy, governments should create safe and responsible environments where students, researchers, and entrepreneurs can experiment with emerging technologies.

Ms. Srour said the future of education will depend on whether institutions can strike a balance between embracing AI and preserving the human capabilities that machines cannot fully replicate.

“I think institutions are becoming more and more aware of the need to keep those skills and develop those skills. The question now is how do we teach our students those skills while at the same time adopting this technology.”

As AI becomes more embedded in classrooms and workplaces, universities may ultimately be judged not by how quickly they adopt the technology, but by whether they continue producing graduates capable of exercising judgment, creativity, and independent thought in a world increasingly shaped by intelligent machines, she added.