AI Patents in the United States and China: Measurement, Organization, and Knowledge Flows

2026-04-12

AI Summary

Existing approaches struggle to accurately identify and compare U.S. and Chinese artificial intelligence (AI) patents, hindering precise assessment of the scale, structure, and knowledge flows underlying AI innovation in both countries. To address this gap, this study fine-tunes the PatentSBERTa model to develop the first AI patent classifier with high generalization performance across both patent systems, achieving a precision of 97.0% and recall of 91.3%. Applying this classifier to granted U.S. patents from 1976–2023 and Chinese patents from 2010–2023, we find that China has recently surpassed the United States in AI patent volume, though its innovators are more fragmented. Despite starkly different organizational innovation models, substantial cross-border citation persists between the two nations, indicating no meaningful technological decoupling in AI.

Technology Category

• Humans and AI: AI for Accessibility
• Philosophy and Ethics of AI: AI & Epistemology
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

We develop a high-precision classifier to measure artificial intelligence (AI) patents by fine-tuning PatentSBERTa on manually labeled data from the USPTO's AI Patent Dataset. Our classifier substantially improves the existing USPTO approach, achieving 97.0% precision, 91.3% recall, and a 94.0% F1 score, and it generalizes well to Chinese patents based on citation and lexical validation. Applying it to granted U.S. patents (1976-2023) and Chinese patents (2010-2023), we document rapid growth in AI patenting in both countries and broad convergence in AI patenting intensity and subfield composition, even as China surpasses the United States in recent annual patent counts. The organization of AI innovation nevertheless differs sharply: U.S. AI patenting is concentrated among large private incumbents and established hubs, whereas Chinese AI patenting is more geographically diffuse and institutionally diverse, with larger roles for universities and state-owned enterprises. For listed firms, AI patents command a robust market-value premium in both countries. Cross-border citations show continued technological interdependence rather than decoupling, with Chinese AI inventors relying more heavily on U.S. frontier knowledge than vice versa.

Problem

• AI patents
• patent measurement
• knowledge flows
• US-China comparison
• innovation organization

Innovation

• Patent classification
• PatentSBERTa
• AI patents
• cross-border knowledge flows
• fine-tuning