TY - GEN

T1 - Design Approaches for Development and Implementation of AI-Driven Government Services

AU - Носиков, Андрей Андреевич

N1 - Conference code: 7

PY - 2025/5/15

Y1 - 2025/5/15

N2 - The relevance of developing government services on artificial intelligence (AI) platforms is becoming increasingly evident within the context of contemporary digital advancement. This article examines the perspectives and opportunities provided by AI platforms for enhancing government services. The research explores global practices of AI application and implementation in government services, enabling the identification of key trends, interdisciplinary scientific research results, and case studies. By employing an integrative review of interdisciplinary scientific sources, implementation cases of AI-driven government services, technical documentation, and regulatory frameworks, the comprehensive conceptualization of designs for implementing AI-driven government services is ensured. The article identifies the main components of various designs for implementing AI-driven government services, facilitating the systematization of different approaches to constructing government AI services. Thus, the article describes a taxonomy of classes of AI-driven government services and addresses the component of Sovereign AI and public-private partnerships. Additionally, an analysis of AI application in the public sector is conducted to identify key areas of application and potential advantages. The obtained results can serve as a basis for developing effective strategies for implementing AI in government agencies, taking into account various specificities.

AB - The relevance of developing government services on artificial intelligence (AI) platforms is becoming increasingly evident within the context of contemporary digital advancement. This article examines the perspectives and opportunities provided by AI platforms for enhancing government services. The research explores global practices of AI application and implementation in government services, enabling the identification of key trends, interdisciplinary scientific research results, and case studies. By employing an integrative review of interdisciplinary scientific sources, implementation cases of AI-driven government services, technical documentation, and regulatory frameworks, the comprehensive conceptualization of designs for implementing AI-driven government services is ensured. The article identifies the main components of various designs for implementing AI-driven government services, facilitating the systematization of different approaches to constructing government AI services. Thus, the article describes a taxonomy of classes of AI-driven government services and addresses the component of Sovereign AI and public-private partnerships. Additionally, an analysis of AI application in the public sector is conducted to identify key areas of application and potential advantages. The obtained results can serve as a basis for developing effective strategies for implementing AI in government agencies, taking into account various specificities.

KW - AI-driven government services

KW - AI government services

KW - taxonomy AI government services

KW - Artificial intelligence

KW - government services

KW - AI

KW - ИИ-ориентированные государственные услуги

KW - государственные ИИ-сервисы

KW - таксономия государственных ИИ-услуг

KW - искусственный интеллект

KW - государственные услуги

KW - ИИ

UR - https://www.mendeley.com/catalogue/0d742cc2-cb64-36b3-b331-a696bb8799ee/

U2 - 10.1007/978-3-031-90720-3_6

DO - 10.1007/978-3-031-90720-3_6

M3 - Conference contribution

SN - 978-3-031-90719-7

T3 - Communications in Computer and Information Science

SP - 77

EP - 92

BT - Digital Transformation in Governance and Society

PB - Springer Nature

T2 - 7th International Conference "Digital Transformation in Governance and Society"

Y2 - 24 June 2024 through 26 June 2024

ER -