1. Introduction
The use of artificial intelligence in higher education is now considered a key driver of the transformation of contemporary teaching and learning. Its presence is reshaping approaches to instruction, the design of learning materials, assessment practices, and the dynamics of the relationship between teachers and students.
However, technology alone does not guarantee success. The effectiveness and meaningfulness of artificial intelligence in education depend on the context in which it is implemented – on the people, institutions, and environments that enable or restrict its use.
To understand the conditions for the successful integration of artificial intelligence in higher education, it is necessary to consider the influence of two interconnected frameworks: the micro-level educational context, which encompasses individual courses, teaching approaches, and student characteristics, and the macro-level educational context, which includes institutional, legal, social, and technological factors.
The following sections examine how these factors interact and shape the real opportunities, challenges, and responsibilities associated with the use of artificial intelligence in higher education.
Particularly important are the perceptions and attitudes of teachers and students, as they largely determine the speed, manner, and extent to which new technologies are adopted within the educational process.

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