Transformative potential of AI in education: сhallenges in developing new conceptual models of pedagogical design

The article explores the transformative potential of artificial intelligence (AI) technologies in education and the key barriers to their integration into pedagogical practice. The authors emphasize that, despite AI’s capacity for personalized learning and its potential to radically rethink educational models, its application often remains limited to technical support for routine tasks, without addressing the fundamental foundations of pedagogical design. The study analyzes classical theoretical models of technology adoption — TAM (Technology Acceptance Model), SAMR (Substitution, Augmentation, Modification, Redefinition), and SCOT (Social Construction of Technology) — identifying their limitations in explaining the socio-professional contexts of AI implementation in education. The core thesis of the work lies in the necessity of synthesizing SAMR and SCOT models to overcome their individual limitations. SAMR provides a framework for analyzing stages of transformation (from substitution to redefinition), while SCOT explains how social negotiations among teachers, administrators, and students influence the acceptance or rejection of technologies. It is demonstrated that fragmented AI implementation stems not only from technical challenges but also from the inertia of the pedagogical community, which clings to pre-digital approaches, as well as fears of algorithmic autonomy and the erosion of educators’ professional roles. The practical significance of the research lies in recommendations for fostering sustainable AI integration practices, including developing teachers’ digital competence, involving them in designing AI tools, and promoting ethical reflection. The authors stress that transitioning to the “redefinition” of educational practices is possible only through social consensus that considers both technological capabilities and the values of the pedagogical community. The article contributes to the development of hybrid conceptual frameworks that combine technological and socio-cultural analysis, potentially opening new directions for research into the symbiosis of human and artificial intelligence in education.