Paper Type
ERF
Abstract
Technology and society are experiencing rapid changes driven by Artificial Intelligence (AI), which is reshaping industries and presenting both breakthroughs and challenges. Nations and organizations are leveraging AI to modernize digital platforms and redefine their identities. As emerging economies like Ethiopia embrace digitalization, understanding AI-driven transformation becomes essential, especially in resource-limited settings. Despite limited AI readiness, Ethiopia's growing digital ambition makes its experiences significant for deeper exploration of AI's impact. Furthermore, while scholars have called for more future-focused research on AI-driven transformation, this field remains underexplored. Therefore, our study aims to examine AI-driven transformation in Ethiopia, utilizing dynamic capability theory and a qualitative case study approach. Based on findings, we will offer recommendations for practitioners, policymakers, and researchers to inform future AI initiatives in the Global South.
Paper Number
1057
Recommended Citation
Ferede, Dereje, "Understanding the Artificial Intelligence (AI)-Driven Transformation of the Global South: The Case of Ethiopia" (2025). AMCIS 2025 Proceedings. 12.
https://aisel.aisnet.org/amcis2025/sig_osra/sig_osra/12
Understanding the Artificial Intelligence (AI)-Driven Transformation of the Global South: The Case of Ethiopia
Technology and society are experiencing rapid changes driven by Artificial Intelligence (AI), which is reshaping industries and presenting both breakthroughs and challenges. Nations and organizations are leveraging AI to modernize digital platforms and redefine their identities. As emerging economies like Ethiopia embrace digitalization, understanding AI-driven transformation becomes essential, especially in resource-limited settings. Despite limited AI readiness, Ethiopia's growing digital ambition makes its experiences significant for deeper exploration of AI's impact. Furthermore, while scholars have called for more future-focused research on AI-driven transformation, this field remains underexplored. Therefore, our study aims to examine AI-driven transformation in Ethiopia, utilizing dynamic capability theory and a qualitative case study approach. Based on findings, we will offer recommendations for practitioners, policymakers, and researchers to inform future AI initiatives in the Global South.
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