The influence of the institutional environment on AI adoption in universities: identifying value drivers and necessary conditions

Purpose In higher education, the appreciation and implementation of artificial intelligence (AI) has led to debate and polarization. This study examines how the institutional environment at universities impacts the value perception and intention to adopt AI in higher education. It seeks to optimize the adoption pathway by identifying essential “must-have factors” and “value drivers.” Design/methodology/approach Employing the technology-organization-environment (TOE) framework alongside the technology acceptance model (TAM) framework and perceived value concepts, this research utilizes a partial least squares structural equation modeling (PLS-SEM) approach complemented by necessary condition analysis (NCA), a novel approach in this context, which allows us to distinguish between critical antecedents and value drivers in the evaluation and adoption of AI technology. Findings Results indicate that organizational complexity, readiness, competency, compatibility and competitive advantage significantly affect the perceived value of AI, mediated by stakeholders’ perceptions of its ease of use and usefulness. These factors enhance the intention to adopt AI in higher education. Perceived usefulness has the highest effect size and the importance of ease of use differs between Europe and South America. External factors like partner support and competitive advantage are necessary considerations to be met, while competitive advantage and some internal factors are sufficient conditions for AI adoption. Originality/value The study underscores the importance of certain institutional factors, setting priorities for management actions in AI adoption. It differentiates between the general appreciation of AI and the intention of practical implementation, highlighting the role of partner support as a necessary condition, although a non-value-driving factor.