From uniqueness to necessity: do academic institutions in developing countries want to adopt artificial intelligence?

Purpose This study examines the determinants of artificial intelligence (AI) adoption in higher education institutions in Iraq as a representative developing-country context. It extends the technology–organization–environment (TOE) framework by incorporating educational readiness, socio-cultural support and international cooperation to better capture contextual factors influencing AI adoption. Design/methodology/approach A quantitative cross-sectional research design was employed. Data were collected through an electronic questionnaire administered to 295 respondents with relevant academic and professional backgrounds. After excluding 34 incomplete or inconsistent responses, 261 valid questionnaires were retained for analysis. Structural equation modeling (SEM) was used to test the proposed research model and examine the relationships among the study variables. Findings The results indicate that technological, organizational and environmental factors significantly influence AI adoption. In addition, educational readiness, socio-cultural support and international cooperation were found to be significant predictors of AI adoption, highlighting the importance of contextual and institutional factors in facilitating AI implementation within higher education institutions in developing countries. Practical implications The findings provide practical guidance for academic institutions and higher education policymakers in developing countries by identifying the organizational, technological, educational, socio-cultural and international cooperation factors that shape AI adoption. The results highlight the need to strengthen digital infrastructure and human capabilities, foster responsible AI cultures and develop international partnerships to support sustainable AI adoption in higher education. Originality/value This study extends the TOE framework by integrating educational readiness, socio-cultural support and international cooperation into the analysis of AI adoption. It contributes empirical evidence from Iraq and provides a broader understanding of the factors shaping AI adoption in higher education institutions operating in developing-country environments.