The rapid expansion of emerging technologies, particularly artificial intelligence (AI), has subjected education-oriented organizations to profound transformations and complex challenges in the process of innovation adoption. The purpose of this study is to design and propose a structural, hierarchical, and non-linear model to identify and explain the causal relationships among the factors influencing the adoption of AI-driven innovations in such organizations. Unlike conventional linear and technology-centered models such as the (TAM) and the (UTAUT), the proposed model adopts a systematic and holistic perspective by elucidating multi-layered causal relationships underlying AI innovation adoption.This applied research employs a mixed-methods approach, integrating qualitative and quantitative phases. Thirteen key factors were identified through a systematic literature review and subsequently analyzed using Interpretive Structural Modeling (ISM), through which they were organized into seven hierarchical levels. Model validation and the assessment of variables’ driving and dependence power were conducted using MICMAC analysis. The findings reveal that perceptual and information-processing infrastructures constitute the most fundamental and influential driving forces, forming the foundation for other components such as digital motivational mechanisms, organizational transformation frameworks, and structural dynamism. The MICMAC results further confirm the structural stability of the system and the clarity of causal relationships among variables. By offering a multidimensional analytical framework, the proposed model provides practical guidance for policymakers and organizational leaders to allocate strategic resources toward the development of perceptual and information-processing infrastructures rather than focusing on superficial instrumental layers. This approach not only prevents resource misallocation but also facilitates the sustainable and effective adoption of artificial intelligence within education-oriented organizations.