利用专利数据识别新兴AI技术：一种半自动化方法

A SEMI-AUTOMATED APPROACH TECHNICAL PAPER September 2025 This work is published under the responsibility of the Secretary-General of the OECD. The opinions expressed andarguments employed herein do not necessarily reflect the official views of the Member countries of the OECD. Thisdocument, as well as any data and map included herein, are without prejudice to the status of or sovereignty over anyterritory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use ofsuch data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlementsin the West Bank under the terms of international law. Note to Delegations: This document is also available on O.N.E under the reference code: Cover image: ©your/Shutterstock.com © OECD 2025 Attribution4.0International (CCBY4.0) This work is made available under the Creative Commons Attribution4.0 International licence. By using this work, you accept to be bound by the termsof this licence (https://creativecommons.org/licenses/by/4.0/). Attribution–you must cite the work. Translations–you must cite the original work, identify changes to the original and add the following text:In the event of any discrepancy between theoriginal work andthe translation, only the text of the original work should be considered valid. Adaptations–you must cite the original work and add the following text:This is an adaptation of an original work by the OECD. The opinions expressedand arguments employedin this adaptation should not be reported as representing the official views of the OECD or of its Member countries. Third-party material–the licence does not apply to third-party material in the work. If using such material, you are responsible for obtaining permissionfrom the third party and for any claims of infringement. Any dispute arising under this licence shall be settled by arbitration in accordance with the Permanent Court of Arbitration (PCA) Arbitration Rules2012.The seat of arbitration shall be Paris (France). The number of arbitrators shall be one. Abstract This technical paper introduces a novel methodology for identifying “AIpatents”—patents protecting inventions related to artificial intelligence (AI).It builds on existing taxonomies and considers recent developments in thefield, notably the surge of generative AI technologies. It combinestechnology groups of the Cooperative Patent Classification (CPC) with a listof AI-related keywords and phrases. The method for identifying AIvocabulary and CPC classes is designed to enable easy updates andintegration of emerging AI technologies. Keywords:Artificialintelligence; Innovation; PatentsJEL Code:O33, O34 Acknowledgements The authors thankFlavio Calvino, Antoine Dechezleprêtre, Guy Lalanne, Karine Perset,Molly Lesher andLucia Russofor their support throughout this project and for their insightful feedback. They are thankful toexperts from theGPAI Expert Communityand to patent examiners from IP Australia and from the FrenchInstitut National de la Propriété Intellectuelle (INPI) who contributed to the validation of the revised AIpatent taxonomy.They are grateful to comments and suggestionsreceived bydelegates oftheCommitteeon Industry, Innovation and Entrepreneurship (CIIE), the Working Party on Industry Analysis (WPIA), theWorking Party on Digital Economics, Measurement and Analysis (WPDEMA),and the Global Partnershipon Artificial Intelligence (GPAI).Fruitful feedback from Christopher Harrison of the World IntellectualProperty Organization (WIPO) is also acknowledged. The paper was written byHélène Dernis, Luis Aranda,Dominique Guellec (University of Strasbourg) andLufei Liu (independent data scientist). The authors also thank Charles-Édouard van de Putand AndreiaFurtadofortheirsupport. Table of contents 3 Abstract Acknowledgements4 Executive summary8 1 Introduction9 2 Reviewofexisting taxonomiesWIPO (2019)OECD (2020)Country Activity Tacker (2020)USPTO (2021 and 2024)WIPO on Generative AI (2024)Other existing taxonomies 101011111212 3 A novel approach to identifying emerging AI fields13 Enrich the list of AI keywords to capture emerging trendsUse of patent classification systemExpert validationRevised AI patent identification methodology 13141617 4 Recent trends in AI patents18 Evolution of patenting in AILeading countries in AI patents 1819 6IDENTIFYING EMERGING AI TECHNOLOGIES USING PATENT DATA 5 Conclusion and limitations22References23Annex A. Identify CPC codes related to AI25Annex B. New AI search strategy28Annex C. Expert consultation31Annex D. Comparison with previous methodology33Annex E. Method for nowcasting AI PCT patents36Endnotes39 FIGURES Figure3.1. Distribution of patents by “Core AI” CPC groups and AI-related keywords15Figure4.1. Evolution of AI patents, 2010-202318Figur