AI Diffusion in Low Resource Language Countries

• URL: http://arxiv.org/abs/2511.02752v1
• Date: Tue, 04 Nov 2025 17:31:39 GMT
• Title: AI Diffusion in Low Resource Language Countries
• Authors: Amit Misra, Syed Waqas Zamir, Wassim Hamidouche, Inbal Becker-Reshef, Juan Lavista Ferres,
• Abstract summary: Low-Resource Language Countries (LRLCs) have a share of AI users that is approximately 20% lower relative to their baseline.<n> linguistic accessibility is a significant, independent barrier to equitable AI diffusion.
• Score: 10.939989206795047
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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