What does a university teach that AI cannot? — this was the title of a roundtable discussion on the second day of the conference, where Bruno van Pottelsberghe, Rector of Corvinus University, joined Charaf Hassan, Rector of BME, Levente Kovács, Rector of Óbuda University, and Zoltán Kónya, Vice-Rector for Science and Innovation at the University of Szeged (video link here). 

The university leaders outlined a consensus with a business mindset: AI must be integrated into education, research and operations, while the core mission of universities — fostering critical thinking and generating new knowledge — must remain intact. They stressed that human expertise, ethics and creativity are irreplaceable, even though AI tools are already being used to improve translation, student services and administrative efficiency, and have shown tangible benefits in medical and engineering fields. 

When it comes to research and infrastructure, the emphasis is twofold: developing practical tools (such as deepfake detection, financial sustainability analyses and predictive student models), while also expanding data management and computing capacity, including national and international supercomputing collaborations. The academic leaders cautioned that AI amplifies existing knowledge but rarely creates new insights on its own. Investment strategies, therefore, need balance: computing resources, critical research, interdisciplinary partnerships and regulatory frameworks must work together to ensure that AI enhances productivity without undermining academic standards. 

Bruno van Pottelsberghe also underlined the superiority of real educators over AI’s role as a knowledge aggregator: “The teachers we remember as truly great are those who challenge their students. That’s something we cannot expect from artificial intelligence.” 

Leadership, cooperation and higher education challenges 

At the conference, György Drótos, Associate Professor at the Corvinus Institute of Strategy and Management, gave a lecture entitled You mustn’t be afraid of AI, it will be good — Perceptual biases and real leadership challenges (available to watch here in Hungarian). He argued that debates around AI are shaped not only by the technology’s complexity, but also by social narratives and status markers associated with it. 

Experience shows that new technologies often follow a curve of hype, inflated expectations and correction. Early adoption tends to reveal shortcomings — such as hallucinations, gaps in data infrastructure and governance — which in turn trigger regulatory responses, investor caution and legal disputes. Meanwhile, organisations and universities also adapt: exam formats, business models and collaboration methods evolve. For leaders, the key is a practical strategy: establish targeted governance, validate business cases, develop the necessary skills, and involve reliable external partners. They must also prepare for fluctuations — periods of rapid uptake, but also times when AI may be harder to access — while striving for sustainable, long-term value creation. 

Róbert Pintér, Associate Professor at the Corvinus Institute of Data Analytics and Information Systems, explored the prospects of human–machine cooperation in his talk AI + human intelligence = new corporate logic? (video available here in Hungarian). He argued that instead of focusing on competition between people and AI, the emphasis should be on collaboration. The debate around automation should not be about who wins — humans or machines — but how to design cooperative workflows. He stressed that just because something can be automated, it does not mean it should be. 

His conclusion for companies was that, since a large proportion of Hungarian SMEs suffer from a lack of data and remain heavily reliant on Excel, AI-driven transformation will only succeed with process-level restructuring, a conscious strategy and long-term cultural change — often taking decades. His recommendation: deliberately choose which tasks to keep, which to delegate, and integrate ethical, regulatory and governance principles into digital transformation plans. 

Anna Orsolya Pongor-Juhász, educational quality development and methodology expert at the Corvinus’ Centre for Teaching and Learning, joined the roundtable Preparation instead of prohibition – How can AI become an ally in education? together with Zsolt Almási, Associate Professor at the English and American Studies Institute of Pázmány Péter Catholic University, Károly Nehéz, Director of the Institute of Informatics at the University of Miskolc, and Sarolta Osztroluczky, Assistant Professor of Literary History at Pázmány Péter Catholic University. 

The speakers agreed that higher education is facing rapid adaptation: the rise of large language models fundamentally challenges traditional student–teacher roles and assessment methods. After initial bans, many institutions are now choosing to integrate AI use through workshops, courses and pilots. Central questions include institutional regulation, detecting academic misconduct and ensuring the labour market relevance of programmes. 

The recommended strategy is to rethink teacher training and pedagogical processes, and to introduce tasks that measure process and critical thinking (oral exams, multi-step assessments, or using AI as a tutor). In practice, this requires institutional support, new classroom formats and collections of examples. The goal is clear: AI should not be treated as an enemy, but as a tool — a way to improve graduates’ preparedness for a changing labour market. 

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The AI Summit is organised by IndaMedia Zrt., publisher of Index and premium business outlet Economx. This year, more than 300 speakers contributed across more than ten thematic sections. Most of the presentations are available for replay via the Indaevents app. 

via Indaevents/Corvinus University of Budapest