In a landscape where digital technologies and AI are transforming industry and how value is created, the way we work—and the professional skills required—are also evolving. On April 17, Dr. Lourdes Perea Muñoz, Vice-Rector of Academic Affairs at the University and A professor from the Digital Transformation Center of the Faculty of Engineering gave a lecture in Portugal on this topic in the context of CPSL: Conference on Production Systems and Logistics.

During the lecture, he reflected on the changing role of universities, the meaning of work, and the curricular adaptations needed to prepare professionals who can remain relevant and contribute significantly in an environment defined by accelerated change and the rapid obsolescence of technical knowledge.

We consulted Dr. Lourdes Perea about the main points of her conference, and shared her perspective on the impact of AI on Higher Education.

What is your view on the inability or slowness - frequently pointed out by the media - of universities in adapting to the changes brought about by technological advances?

While I agree with the need for universities to adapt (I teach about digital transformation management), I believe that an overly fatalistic or superficial approach can divert attention from what is truly important: thinking about this adaptation in light of its purpose.

I see this same phenomenon in companies; I perceive a great fear of being left behind, and that leads them to think first about how to adopt AI, rather than why to adopt AI. But I think that in the case of universities this is even more critical than in the business world, because universities encompass very diverse activities and their mission is much more complex.

People talk about FOMO, what causes that effect?

We are all experiencing, on a personal level, the extraordinary power of these generative AI models. The level of sophistication of the results with almost no effort, the increase in productivity, the improved quality of output for certain tasks, and the ease with which we can expand our capabilities in areas outside our own expertise are remarkable. coreThis puts us on alert and makes us think about our own need to adapt. Not only that, but AI's capacity for constant improvement is also evident; as soon as it encounters a barrier or error, a new model is quickly developed that seems to have overcome it.

If, in addition to our bewilderment, we seek someone very close to the discipline: AI specialists, computer or systems engineers, specialists who are ahead in these matters, they also fail to transmit much peace to us; one returns with more anxiety, because they themselves are astonished.

However, the experience is quite different when scaling up. According to a recent MIT study, 95% of AI pilot projects at the organizational level are failing. But why? Because that apparent simplicity masks a redistribution of complexity to other areas of the organization, making the path to real value much more arduous. When these solutions are implemented at the enterprise level, a series of structural needs and complexities emerge that deflate the illusion of immediate productivity. New areas of need arise (such as data governance, engineering, and...) prompting, compliance and confidentiality); the need arises to redesign workflows where humans and teammates Cybernetic systems are interacting, and the need to develop new, complementary skills in people to monitor the (not always accurate) results of AI is becoming evident. It's clear that the adoption of AI, and especially the realization of its value in companies, will not be without its share of disappointments.

Doesn't this mean we can rest easy?

One thing is certain: the adoption rate of AI will continue to rise, with more and more applications and use cases emerging. As Dr. Samila (IESE) explains, this follows from the logic that AI reduces the costs of generalist knowledge. input Fundamental to the knowledge economy, just as steam power once reduced the cost of mechanical energy, a key input in the economy of industrial society. What we can expect, then, is that the use of AI will continue to increase; that new use cases will be discovered; that many current jobs performed by humans will gradually be replaced, while others will emerge; but, above all, that professional competence will depend largely on new human skills that complement the potential of AI: metacognitive skills (analytical, systemic, and creative thinking), collaborative skills (leadership), and ethical skills.

The future of work will be neither purely automated nor purely human. It will be a network of hybrid teams, where people will need to orchestrate, monitor, and make sense of increasingly intelligent systems.

The real university challenge

It's clear that universities, like businesses, can benefit from adopting AI: management processes can be reviewed in light of AI, as can teaching practices and research. But in my view, there's a more central challenge than mere adoption. And that challenge has to do with the university's mission.

When universities are criticized in general, the focus is on the gap between students' current preparation and the world of work. But this view reduces the university to a mere certifier of knowledge. Is its mission only to prepare students for their first job? It is that, but it doesn't end there.

The university, “is the place where knowledge lives, interacts, and evolves” (quote from Professor Zheng of Columbia, referencing the writings of J.H. Newman). And here, I want to focus on the verbs that accompany the word knowledge:

Knowledge livesEvery discipline has a domain, a set of methodologies, and a community of practitioners (academics, researchers, students) who together represent that living reality. AI affects different disciplines in different ways; in some cases, it changes their specific domain, and in others, only their methodologies or tools. It is this community of experts that can interpret where a discipline might be affected and make the necessary changes, in the place where these changes become structural: the curricula. It is in these curricula that the path of what it means to “expertise"in a discipline, and it is through these that future members of the disciplinary community will be trained."

Knowledge interacts: Knowledge itself is not a fragmented reality; we fragment it into specialties in order to make progress and understand it within our limited capacity. But the university is the place where different disciplines interact, achieving not only advancements for society but also an integrated synthesis. That is, helping students formulate an interpretation of the world and reality that gives it meaning. If digital transformation brings new ways of creating value, what is the true meaning of value? Is it only greater efficiency and productivity? Is it a better employee experience? Is it a solution to more complex social problems?

Knowledge evolves: Knowledge evolves based on intellectual advancements, as we mentioned, but it also evolves due to social demands, often triggered by the impact of technological progress. This ensures that technological advancement remains connected to the purpose of progress for humanity. Should everything that can be done be done? Or will evolution truly seek progress for humanity? The evolution of knowledge cannot occur in isolation from its purpose.

Therefore, in addition to technical knowledge, the University also has as its mission the formation of people with wisdom: that is, with the capacity for judgment, discernment, with a deep ethical commitment and also with leadership in such a way as to guide themselves and guide others towards what is truly good for humanity.

These are precisely the complementary aspects to AI that will be valued in the future. These are the skills that various reports on the future of work (such as the WEF's "The Future of Work 2025") identify as future capabilities: analytical, systemic, and creative thinking, self-efficacy, and leadership. But, at the same time, this is what is being put into "check" Yes, responding to demands for agile adaptability, universities are embarking on a race to rapidly change their curricula to meet the immediate needs of the job market. The development of these skills relies on the formation of fundamental knowledge in the disciplines, humanistic skills, and is also necessarily acquired gradually through the enriching experience of university life.

And it is precisely in this way that the University ultimately acts as culture generatorWe talk about the future of work, but as Professor Asla (Austral) said, the future doesn't yet exist; the future is built by the actions of people: free people. Therefore, while the University navigates its own path of adapting to change, it must not abandon its ultimate mission of serving society and the common good. The university has to adapt to change, but at the same time it can shape change.

How are we addressing this in the Universidad Austral?

Several projects in our strategic plan are coordinated to prepare our students for this future.

On the one hand, the flexibility of study plans. Through this project we have sought to provide our study plans with a semi-structure that allows two things:

First, separate the more foundational knowledge of the disciplines: that which does not change and allows students a deep understanding so they can quickly adapt to technological changes and changes within the discipline itself. And a flexible part, which allows for the constant updating of those more tool-based or technological aspects that, in this context, are becoming increasingly obsolete.

The second aspect that this flexibility allows is a certain space for more personalized pathways, according to the interests and aptitudes of our students, as well as for a more interdisciplinary dialogue, that is, the possibility of taking courses from other degrees and putting different perspectives into dialogue.

Another key project in this context is that of intellectual virtuesLed by the Institute of Philosophy and involving over 200 professors, this project aimed to highlight the need for cultivating the virtues that define a good thinker. These virtues also form the basis for developing the skills of the future. For example, analytical thinking requires not only solid knowledge but also virtues such as rigor, attentiveness, depth, and open-mindedness. And so on, we could connect the various intellectual virtues with the different skills outlined in the WEF report.

Furthermore, the strengthening of humanities subjects of our curriculum, a key aspect so that our students can, beyond their own discipline, generate a deep and meaningful understanding of the world. That they are capable of asking profound questions such as the meaning of work and of business.

TAI-certified College lifeWith its diverse proposals, the interdisciplinary approach it offers, and the various activities it carries out with the university community, many of them are aimed at strengthening positive behavioral values ​​(honesty, solidarity) and fostering social awareness and commitment.

And finally, the explication of our educational model, which seeks to present in a coordinated way how the different aspects recently mentioned are aligned with the purpose of forming graduates with a differentiated profile: excellent professionals and at the same time, excellent people who can exercise human, intellectual and social leadership in their environment.

It is also worth mentioning that, in parallel with all of this, from the teacher training offered by the Innovation Department, we consider it important to... training of our teachers in AI topics, and exploration through innovation labs, to better understand how AI can help enhance classes, assessments and student monitoring, always from the perspective of our educational model.