Navigating institutional and capability barriers in agentic artificial intelligence adoption: evidence from small and medium enterprises in Bangladesh

PurposeThis study aims to explore the barriers and solutions associated with the adoption of Agentic artificial intelligence (AAI) among small and medium-sized enterprises (SMEs) in Bangladesh. AAI, an advanced evolution of generative AI, offers potential for enhanced knowledge sharing, autonomy and organizational performance, yet its adoption in developing economies remains poorly understood. Drawing upon institutional and dynamic capabilities theories, this study investigates how contextual, structural and capability-related factors influence AAI adoption.Design/methodology/approachA qualitative research design was used, involving 14 semi-structured interviews with SME owners, technology experts and government officials in Dhaka, Bangladesh. Thematic analysis was used to identify key barriers and solutions, supported by triangulation, peer debriefing and member checking to enhance credibility.FindingsThe analysis identified eight primary barriers: slow internet speeds, limited knowledge and skills, inadequate infrastructure, lack of government support, political instability, high adoption costs and absence of a legal framework. To overcome these challenges, participants proposed developing awareness and education programs, building technological infrastructure, improving internet connectivity, establishing supportive legal and policy frameworks, offering financial incentives, fostering public-private partnerships and integrating AAI education into academic curricula. These findings reveal that AAI adoption is shaped not only by firm-level readiness but also by institutional and ecosystem maturity.Originality/valueTo the best of the authors' knowledge, this research is among the first to examine AAI adoption in SMEs within a developing economy empirically. By combining institutional and dynamic capabilities theories, this study contributes to the growing literature on intelligent systems, offering a holistic framework that links institutional context, organizational capability and knowledge management to AAI adoption in emerging markets.