Factors of using generative artificial intelligence in the design of educational products

The relevance of the research is due to the rapid development of generative artificial intelligence (GenAI), which opens up new opportunities for designing educational products, as well as the growth of institutional and financial investments of educational organizations in AI technologies, the effectiveness of which is largely determined by factors of professional acceptance. Despite GenAI’s high technological potential, there remains a significant gap between its capabilities and actual integration into educational design processes, which creates managerial and economic risks of inefficient use of digital innovations. The aim of the work is to identify and analyze the key factors determining the introduction of GenAI technologies into educational design processes in higher education institutions from the standpoint of the theory of technology adoption and digital transformation management. The methodological basis of the study was the extended model of the Unified Theory of Acceptance and Use of Technology (UTAUT), supplemented by the author' construct «Intellectual Trust». The empirical verification of the hypotheses was carried out using a quantitative survey of 54 specialists from Russia and Latin American countries and Partial Least Squares Structural Equation Modeling (PLS-SEM). It was found that perceived ease of use (β = = 0.310; p < 0.05) and intellectual trust (β = 0.348; p < 0.05) are key determinants of behavioral intent and jointly explain 30.6% of its variance, while the expected usefulness and intention of use have a significant impact on the actual use of GenAI; the model explains 47.8% of the variance of use. The scientific novelty lies in the empirical validation of intellectual trust as a critical factor in the adoption of GenAI and the identification of the absence of direct influence of social and technical and organizational factors of the UTAUT in this professional context. The practical significance of the research is to substantiate managerial approaches to the integration of GenAI, focused on proving the professional usefulness of technology and building trust in algorithmic solutions.