RETHINKING UNIVERSITY TEACHING WITH AI: INSTRUCTIONAL INNOVATION, IMPACTS, AND PERSPECTIVES

Abstract

In recent years, artificial intelligence (AI) has established itself as one of the main drivers of transformation in contemporary society, profoundly affecting sectors such as medicine, industry, communication and, increasingly, higher education. The spread of technologies based on machine learning, natural language processing and neural network algorithms is helping to redefine not only the ways in which information is accessed, but also the teaching-learning processes, teaching practices and organizational models of universities (Holmes & Tuomi, 2022; Crompton & Burke, 2023; Zawacki-Richter et al., 2019).

In the academic context, AI is progressively explored as a tool for educational innovation, capable of supporting the personalization of training pathways, improving the effectiveness of assessment and expanding opportunities for inclusion (Luckin et al., 2016; Chen et al., 2020). At the same time, its dissemination raises relevant questions on a pedagogical, ethical and social level, in relation to the quality of learning, the role of teachers, data management and possible inequalities of access. The university thus finds itself at the center of a tension between opportunities for renewal and the need to critically govern the adoption of emerging technologies (UNESCO, 2021).

Numerous studies show that AI tools are now widely adopted among university students, particularly to support information search, academic writing, and content synthesis (Bughin et al., 2018; Jereb & Urh, 2024). However, in the face of this diffusion, a significant gap emerges between the actual use of technologies and the possession of critical and conscious skills, highlighting the need to strengthen AI literacy and to integrate these tools in a structured way into university curricula (Holmes, Bialik & Fadel, 2019). This discrepancy prompts a broader reflection on the role of the university not only as a place of technological adoption, but as a space for critical and responsible training.

In this scenario, AI contributes to questioning two fundamental questions of university teaching: what to teach and how to teach. On the one hand, the increasing automation of basic cognitive tasks reduces the exclusive value of static knowledge transmission; on the other hand, the need to develop higher-order skills, such as critical thinking, problem solving, collaboration and ethical responsibility is reinforced (Center for Curriculum Redesign, 2015; Rivoltella, 2019; Nuzzaci, 2025). The university is therefore called upon to rethink its educational objectives, orienting itself towards educational models capable of integrating disciplinary knowledge, transversal skills and meta-skills.

This paper aims to analyze the role of artificial intelligence as a lever of educational innovation in higher education, highlighting its potential, applications and limitations. In particular, the impact of AI on teaching-learning processes, the main educational technologies and applications, the change in the role of the university teacher and the ethical, social and cultural implications related to its adoption are examined (Panciroli & Rivoltella, 2023; Baker & Hawn, 2021). The goal is to outline a critical and integrated vision, in which AI is not considered as an end in itself, but as a tool to be governed in a conscious and responsible way, at the service of the quality and equity of university education.

The paper adopts a narrative-argumentative theoretical-critical approach, based on a selective review of the international literature on Artificial Intelligence in Education (AIED). The analysis integrates pedagogical, technological and ethical contributions, with the aim of building an interpretative framework useful for university teaching design.