AI in Ethiopia: Progress Analysis Technique and Recommendations for Implementing Sustainable Development

This study examines two artificial intelligence (AI) issues. First, we examine the sustainable development challenges and workarounds of AI and offer policy recommendations. We applied the “strategy-as-practice” framework and collected input from expert interviews and secondary sources. With this, we respond to three AI challenges: developing AI infrastructure and data management, developing an AI workforce and localized innovation, and building AI awareness and policy frameworks. Second, we propose a 2 × 3 framework that looks at the pros and cons of the three facets of AI—autonomy, learning, and inscrutability. This enables managers and policymakers to assess their institution's or country's AI progress, mapping what they are doing (pros) and what they are overlooking (cons) in the 2 × 3 framework. The study examines how these responses are shaped by the practices and involvement of both AI and non-AI practitioners. These insights contribute to the literature on information systems strategy, policy, responsible AI, and AI operationalization.