U.S.-China Competition for Artificial Intelligence Markets: Analyzing Global Use Patterns of Large Language Models

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Authors: Austin Horng‐En Wang, Kyle Siler-Evans
Cited by: 0

Abstract

The authors analyze global large language model (LLM) adoption patterns of U.S. and Chinese models and explore three key drivers of international LLM adoption: pricing strategies, multilingual capabilities, and government-led diplomacy initiatives. The authors aim to provide insights to policymakers, technology leaders, and industry observers who seek to understand the evolving U.S.-China competition for artificial intelligence supremacy.

Fields of Study & Subjects

COVID-19 Geopolitics Technology Migration Topic Modeling Ethics and Social Impacts of AI

Publication details

Journal / source
RAND Corporation eBooks
Publication date
1 January 2026
Language
EN
Document type
Book