Quality of Education in the Face of Automation and Artificial Intelligence

Abstract

The intensification of automation and the rapid development of artificial intelligence (AI) profoundly transform contemporary educational systems, altering established standards in the field of education quality and generating new requirements regarding the competencies of students and teaching staff. The relevance of the researched topic is determined by the increasingly widespread application of digital tools, the pressure to integrate AI into teaching–learning processes, and the need to provide a balance between innovation adoption, ethics, and equity. In the year 2025, discussions about the quality of educational services can no longer be separated from a thorough analysis of how AI impacts personalized learning, outcome assessment, data management, and the redefinition of the teachers role in education. The aim of the research is to examine how artificial intelligence and automation affect the quality of education, highlighting both the opportunities and the risks that have a systemic impact. The study seeks to identify the conditions under which AI supports the improvement of student outcomes and enhances the efficiency of teaching activities, as well as to point out the barriers that already compromise equity, relevance, and ethics in education. The research methods used include a comparative analysis of recent international literature (UNESCO, The Guardian, the U.S. Department of Education), as well as the results of opinion surveys. Reports, data on the implementation of AI solutions, and feedback from teaching staff involved in the application of AI for various educational needs are also examined. The research results indicate that AI makes a significant contribution to improving the quality of education when it is used to personalize students learning pathways, provide feedback, identify learning gaps in a timely manner, and optimize teachers time. Students with lower performance can benefit from adaptive learning, while teaching staff can focus their efforts on higher-level formative activities. However, research on AI in education also reveals substantial challenges: major dependence on technologies may reduce the depth of young peoples critical thinking; digital inequalities may intensify in the absence of adequate resources; and the lack of pedagogical training for the use of AI in assessment or in generating educational resources generates fear, stress, and resistance among teachers. Moreover, risks related to data protection and the ethics of AI use require clear, effective, and result-oriented regulations and international standards. The conclusions indicate that the impact of AI on the quality of educational services is profound and dual in nature: the technology offers significant positive outcomes, yet only those educational systems that design and implement responsible AI policies, invest in teacher training, and develop ethical governance mechanisms will be able to transform AI into an effective tool for improving the quality of education, rather than into a factor of risk or imbalance in the existing state ofaffairs. UDC: [37.01:005.336.3]:004.8; JEL: I21, I23, I25, O30, O33