在社会保障中利用人工智能：用例、治理和劳动力就绪度

Harnessing Artificial IntelligenceinSocial Security Use Cases, Governance andWorkforce Readiness Harnessing ArtificialIntelligence in Social Security USE CASES, GOVERNANCE AND WORKFORCEREADINESS This work was approved and declassified by the Public Governance Committee on 29/11/2025. This document was produced with the financial assistance of the European Union. The views expressed herein can inno way be taken to reflect the official opinion of the European Union. This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty overany territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. OECD (2025),Harnessing Artificial Intelligence in Social Security: Use Cases, Governance and Workforce Readiness, OECDDigital Government Studies, OECD Publishing, Paris, https://doi.org/10.1787/b52405c1-en. ISBN 978-92-64-83504-7 (print)ISBN 978-92-64-69427-9 (PDF)ISBN 978-92-64-63541-8 (HTML) OECD Digital Government StudiesISSN 2413-1954 (print)ISSN 2413-1962 (online) Photo credits:Cover © shurkin_son/Shutterstock.com Corrigenda to OECD publications may be found at: https://www.oecd.org/en/publications/support/corrigenda.html.© OECD 2025 Attribution 4.0 International (CC BY 4.0)This work is made available under the Creative Commons Attribution 4.0 International licence. By using this work, you accept to be bound by the terms of 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 the original work and thetranslation, 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 expressed and arguments employed inthis 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 permission from the third party and forany claims of infringement.You must not use the OECD logo, visual identity or cover image without express permission or suggest the OECD endorses your use of the work.Any dispute arising under this licence shall be settled by arbitration in accordance with the Permanent Court of Arbitration (PCA) Arbitration Rules 2012. The seat of arbitration shallbe Paris (France). The number of arbitrators shall be one. Foreword Artificial intelligence (AI)systems may beusedto improve access tosocial securitybenefits,getting theright benefits to the right people at the right time. Adopting AI technology may also complement broaderpublic sector efforts to enhance productivityand deliver more user-centred and proactive services. Toexplore how AI can be used to this end,themainsocial security institutions of France(theCaissenationale des allocations familiales–CNAF, theCaisse nationale de l’assurance maladie–CNAM, andtheMutualité Sociale Agricole–MSA)andItaly(theIstituto nazionale della previdenza sociale–INPS)have engaged in a collaborative project,funded by the European Union via the Technical SupportInstrument, and implemented by the OECD, in co-operation with the European Commission. Theinstitutions undertaking this projectare alreadytestingAI applicationsin a variety of functions, suchasenhancing internal knowledge management, improving communication with existing and potentialbeneficiaries, and supporting data analysis, while still proceeding cautiouslygiventhe high-risk designationunder the EU AI Actfor many use cases. The purpose of this report is to provide a curated set of international good practices to guide future AIadoption, based on gaps and challenges identified in theearlier gap analysis report developed by theOECD. The report also documents concrete policy levers, tools, implementation strategies, and capacity-building efforts relevant to public service contexts at the national level, with particular attention to issues ofdata quality, governance, and workforce readiness. It aims to provide a guide on how the social securitysector can benefit from and align with national efforts for more cohesive, impactful and trustworthy uses ofAI.Further efforts will be neededto explore the effective use of AI in the social security sector, particularlyin adapting these practices to the specific operational, legal, and ethical contexts of social protectionsystems. Continued experimentation, evaluation, and cross-sector collaboration will be essential to ensurethat AI adoption delivers tangible benefits while safeguarding equity, transparency, and public trust. Ultimately, this work underscores a critical opportunity to harness AI as a strategic enabler of moreinclusive, effective, a