Publication Details
Abstract
The rapid digitalization of higher education has placed software platforms and artificial intelligence (AI) at the center of how the educational process is planned, delivered, and evaluated. This article examines the ways in which learning management systems, intelligent tutoring systems, automated assessment tools, predictive analytics, and generative AI assistants are being integrated into the organizational architecture of teaching and learning. Using a qualitative, literature-based analytical design combined with a comparative case analysis of widely adopted platforms, the study develops a functional classification of software and AI tools according to the stage of the educational process they support: curriculum organization, instructional delivery, assessment, and institutional administration. The findings indicate that AI-enabled personalization and automation can improve the efficiency, consistency, and accessibility of the educational process, while simultaneously raising challenges related to data privacy, algorithmic bias, the digital divide, and the professional readiness of teaching staff. The article concludes with a set of practical recommendations for higher education institutions seeking to integrate software and AI tools in a pedagogically sound and ethically responsible manner, and it outlines directions for future empirical research.