The presence of artificial intelligence (AI) and machine learning (ML) in higher education is no longer merely a technological novelty. It is increasingly becoming an issue of educational organisation and pedagogy. Functions such as designing adaptive learning pathways, predicting student performance, and providing automated feedback can enhance the efficiency of instruction and support students’ personal development. AI-based systems such as chatbots, automated assessment platforms, or intelligent tutoring applications can analyse learner data in real-time, offering tailored support to instructors and students. This becomes especially valuable when the goal is not only the transmission of knowledge but also its deeper understanding and long-term retention. At the same time, technology is not a cure-all. The use of intelligent systems raises several new challenges, including concerns about data protection, technical flexibility, and the redefinition of the teacher-student relationship. Drawing on insights from the WTCAi research, this paper presents development directions to ensure AI systems do not function as isolated educational units but as integrated solutions that align with existing curricula [9, 10]. In this context, artificial intelligence appears as a tool and a new educational perspective. It supports a learning culture that places student autonomy, personalised learning, and pedagogical flexibility at its centre.