Validation of challenges for the adoption of artificial intelligence in higher education considering the context of an emerging economy country

Purpose This study aims to identify and validate the main challenges associated with the adoption of artificial intelligence (AI) in teaching and research at the higher education level, considering the context of an emerging economy. Design/methodology/approach The research employs a systematic literature review and a survey with higher education experts in Brazil. The Lawshe method was applied to validate the identified challenges, using a mixed qualitative-quantitative approach. Findings The study validates three critical challenges for AI adoption: lack of knowledge about AI, limited access to technological equipment, and insufficient training for the use of technologies. These factors highlight significant barriers to integrating AI into teaching and research. Although seven additional challenges were not validated, they remain relevant in broader discussions about AI implementation. Research limitations/implications The results are specific to the Brazilian context and cannot be generalized to other contexts with different characteristics and specificities. The results achieved in this study can serve as a basis for future research that aims to carry out comparative studies between countries to better understand regional and contextual differences in the adoption of AI in education. Originality/value This research addresses an important gap by providing empirical validation of the challenges related to AI adoption in higher education within emerging economies, contributing both practically and theoretically to literature in this context.