Artificial Intelligence Investment in Resource-Constrained African Economies: Financial, Strategic, and Ethical Trade-Offs with Broader Implications

Victor Frimpong ()
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Victor Frimpong: Management Department, SBS Swiss Business School, 8302 Zurich, Switzerland

World, 2025, vol. 6, issue 2, 1-17

Abstract: This paper argues that investing in artificial intelligence (AI) in developing economies involves significant trade-offs requiring ethical, financial, and geopolitical scrutiny. While AI is increasingly seen as a vehicle for technological leapfrogging, such ambitions often mask structural constraints, including weak infrastructure, limited institutional capacity, and external dependency. Using the economic theory of opportunity cost—extended through the political economy and digital governance perspectives—this study critically examines AI policy strategies in Ghana, Kenya, and Rwanda. A qualitative design grounded in secondary data and a thematic analysis reveal how AI investment may reallocate scarce resources away from essential services, exacerbate inequality, and entrench strategic technological dependency. This paper proposes a public policy framework built on four principles—sequential readiness, strategic alignment, ethical governance, and capacity building—to guide equitable AI deployment. It argues for establishing a digital social compact between states, citizens, and technology actors to safeguard public interest in AI-driven development. Finally, this paper outlines a future research agenda emphasizing the mixed-method evaluation of AI’s long-term social impacts, including employment, inclusion, and public service delivery.

Keywords: Africa AI policy; AI trade-offs; digital development; emerging economies; public investment trade-offs; technology and inequality (search for similar items in EconPapers)
JEL-codes: G15 G17 G18 L21 L22 L25 L26 Q42 Q43 Q47 Q48 R51 R52 R58 (search for similar items in EconPapers)
Date: 2025
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