Enhancing public service delivery efficiency: Exploring the impact of AI

服务交付框架 透明度(行为) 背景(考古学) 业务 公司治理 服务(商务) 公共服务 知识管理 过程管理 公共关系 营销 政治学 计算机科学 计算机安全 古生物学 财务 生物
作者
Abhinandan Kulal,Habeeb Ur Rahiman,Harinakshi Suvarna,N Abhishek,Sahana Dinesh
出处
期刊:Journal of open innovation [MDPI AG]
卷期号:10 (3): 100329-100329 被引量:11
标识
DOI:10.1016/j.joitmc.2024.100329
摘要

This study aims to investigate the impact of Artificial Intelligence (AI) adoption on public service delivery efficiency in India. It addresses a significant gap in existing literature by investigating the impact of AI adoption on public service delivery efficiency in India, a context that has not been extensively explored. Through a comparative analysis approach, the study assesses the effectiveness of AI applications in enhancing public service delivery. The quantitative research design employed in the study draws on previous literature on AI integration in governance and focuses on Chief Information Officers (CIOs) as primary respondents. The findings reveal significant improvements in citizen-centric services and municipal processes due to AI adoption. However, the impact on human-centric aspects is found to be moderate. The study also underscores the importance of infrastructure readiness for successful AI implementation. Notably, only 25 % of organizations were found to be possessing advanced technological infrastructure. This research is original in its focus on Chief Information Officers (CIOs) as primary respondents and its comparative analysis approach to assess the effectiveness of AI applications in enhancing public service delivery. This study offers valuable insights for policymakers and practitioners. Emphasizing the need for effective policies and infrastructure development, it highlights the potential of AI to eliminate corruption risks and enhance overall efficiency and transparency in public service delivery mechanisms.

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