AI Adoption Barriers for SMEs in Addis Ababa: A TOE-Based Analysis within the Digital Ethiopia 2025 Framework

This manuscript examines the main barriers limiting artificial intelligence adoption among small and medium enterprises in Addis Ababa. It uses the Technology Organization-Environment framework to organise current evidence and identify practical policy responses.

 

Abstract: Ethiopia’s transition toward a knowledge-based economy has created new opportunities for digital growth, yet small and medium enterprises in Addis Ababa continue to face a significant gap in artificial intelligence adoption. This study uses a qualitative systematic review and the Technology-Organization-Environment framework to synthesise evidence from 2024–2026 institutional and policy sources. The findings show that the main barriers are technological, including high hardware costs and limited access to local-language data; organisational, including low digital literacy and talent shortages; and environmental, including a weak private-sector AI ecosystem and compliance uncertainty. The paper concludes that Ethiopia’s next phase of digital policy should move beyond infrastructure expansion and focus on SME enablement through fiscal support, open local datasets, and affordable AI services.