Paper Type
ERF
Abstract
National security—a cornerstone of state sovereignty—is undergoing significant transformation as rapid advances in AI unlock opportunities and raise questions that challenge traditional practices. Systematically understanding and documenting AI’s implications for national security is therefore essential. This study has two objectives: 1) to review and analyze the national security implications of AI, and 2) to provide policy recommendations for Ethiopia, drawing on international experiences to mitigate risks and harness opportunities. Guided by dynamic capability theory and employing the PRISMA methodology, data will be collected from academic databases. Selected studies will undergo screening based on predefined criteria and qualitative analysis. Next, the study will propose policy recommendations to help Ethiopia develop AI-enabled national security capabilities across three dimensions—sensing, seizing, and transforming—addressing both risks and opportunities. The review seeks to advance scholarship on AI and dynamic capabilities while offering practical guidance for policymakers in Ethiopia and similar contexts.
Paper Number
1162
Recommended Citation
Ferede, Dereje, "From Global Evidence to Local Policy: A Systematic Review of AI’s National Security Implications and Recommendations for Ethiopia" (2026). AMCIS 2026 Proceedings. 8.
https://aisel.aisnet.org/amcis2026/ccris/sig_ccris/8
From Global Evidence to Local Policy: A Systematic Review of AI’s National Security Implications and Recommendations for Ethiopia
National security—a cornerstone of state sovereignty—is undergoing significant transformation as rapid advances in AI unlock opportunities and raise questions that challenge traditional practices. Systematically understanding and documenting AI’s implications for national security is therefore essential. This study has two objectives: 1) to review and analyze the national security implications of AI, and 2) to provide policy recommendations for Ethiopia, drawing on international experiences to mitigate risks and harness opportunities. Guided by dynamic capability theory and employing the PRISMA methodology, data will be collected from academic databases. Selected studies will undergo screening based on predefined criteria and qualitative analysis. Next, the study will propose policy recommendations to help Ethiopia develop AI-enabled national security capabilities across three dimensions—sensing, seizing, and transforming—addressing both risks and opportunities. The review seeks to advance scholarship on AI and dynamic capabilities while offering practical guidance for policymakers in Ethiopia and similar contexts.
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