AI Diffusion to Low- and Middle Income Countries; A Blessing or a Curse?

Rapid advances in AI have incited extensive inquiry into its effects on productivity and labor, potentially profound in both positive and negative ways. Often neglected, however, is comprehension of how AI technologies diffuse across and within economies. Developing nations, in particular, face substantial labor market impacts from either swift AI adoption or diminished competitiveness from sluggish diffusion. This paper examines the literature on technology diffusion and proposes a tripartite framework to elucidate AI diffusion pathways: global value chains, research collaboration, and inter-firm knowledge transfers. Employing these metrics, it evaluates AI diffusion in sixteen lower- and middle-income countries (LMICs) relative to four developed nations and assesses their dependency on the USA and China. Findings reveal a notable gap in AI diffusion between developed and developing economies, though this chasm is gradually closing. China emerges as a vital source of future diffusion via value chains, while the USA wields greater influence through research and knowledge transfers. Limitations include the exclusion of certain data sources and regions, and the absence of quantitative analysis on diffusion's relationship with technology intensity. Nonetheless, the research surfaces critical macro-level considerations about AI diffusion. It advocates mechanisms to redistribute AI-induced economic gains and bilateral agreements to complement international accords, thereby addressing the diverse needs and risks of economies entering an AI-dominated era. Future inquiries should explore the nexus between AI diffusion, technology intensity, and productivity; refine diffusion measurement methods; incorporate case studies and targeted policy recommendations; and delve deeper into LMIC-specific labor market outcomes.