Managerial factors of successful AI implementation in the agricultural sector

In the agro-industrial complex, there remains a gap between the high technological potential and poor implementation of digital solutions into practice. Despite government investments and the advancement of digitalization programs, small and medium-sized enterprises face resource constraints and institutional barriers that slow down the adoption of artificial intelligence (AI) technologies. The scientific problem lies in poorly developed mechanisms clarifying what managerial conditions frame the willingness of agricultural enterprises to transform themselves. The article identifies key factors that ensure the successful adoption of AI in the agricultural sector. The principles of innovation management, the theory of organizational readiness for change, as well as adapted TAM and UTAUT models constitute the methodological framework of the study. The empirical analysis draws upon survey data obtained from executives and specialists of agricultural enterprises (N = 124; the survey period covered June–August, 2025). The work employed the PLS-SEM method. The results indicate that the fundamental conditions for digital transformation in the agricultural sector are the presence of an innovation-oriented culture, adequate resource support, and social influence shaping the perceived usefulness of new technologies among market participants. At the same time, the ease of AI use does not have a significant effect on managerial decision-making. The innovation readiness factors are concluded to be predominantly managerial in nature. The findings can be of use when formulating government support measures, corporate strategies, and practical solutions to accelerate the process of digital transformation in the industry.