AI Diffusion in Low Resource Language Countries

2025/11/04 by Misra, Amit, Zamir, Syed Waqas, Hamidouche, Wassim +2
Computer Science · Social Sciences · #ICT in Developing Communities #Language and cultural evolution #Economic Growth and Development

paper · doi:10.48550/arxiv.2511.02752

Abstract

Artificial intelligence (AI) is diffusing globally at unprecedented speed, but adoption remains uneven. Frontier Large Language Models (LLMs) are known to perform poorly on low-resource languages due to data scarcity. We hypothesize that this performance deficit reduces the utility of AI, thereby slowing adoption in Low-Resource Language Countries (LRLCs). To test this, we use a weighted regression model to isolate the language effect from socioeconomic and demographic factors, finding that LRLCs have a share of AI users that is approximately 20% lower relative to their baseline. These results indicate that linguistic accessibility is a significant, independent barrier to equitable AI diffusion.

Citations

• Measuring AI Diffusion: A Population-Normalized Metric for Tracking Global AI Usage
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