Identification and Modeling of Artificial Intelligence Functions in Enhancing the Efficacy of the Administrative System and Public Service Delivery

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Providing appropriate public services plays a vital role in improving public efficacy and governance quality. In this context, leveraging artificial intelligence (AI) in public administration can enhance decision-making quality in the public sector, improve the efficacy of public service delivery to citizens, and increase their satisfaction with governance. Accordingly, this study aims to identify the functions of AI in enhancing the quality of public services. Based on a review of scientific literature in the field of AI functionalities and using thematic analysis, 11 fundamental AI functions for improving administrative systems were identified. In the next phase, the identified functions were structured into four levels using the Interpretive Structural Modeling (ISM) method. Among these, data-driven decision-making facilitation in the public sector emerged as the foundational function at the fourth level, recognized as the most critical AI functionality for enhancing administrative efficacy. Additionally, functions such as improving service quality and economic productivity, reducing the costs of ill-informed decisions, and enhancing transparency, accountability, and public trust were identified as the primary outcomes of AI, categorized at the first level. Furthermore, functionalities including process automation and intelligence, leveraging collective intelligence and increased citizen engagement, personalized service delivery, enhancing the quality and intelligence of human resource management, intelligent diagnosis in public service delivery, and enabling inter-organizational smart interaction were identified as pivotal variables with leverage effects in achieving AI-driven administrative efficacy and public service delivery.

Language:
Persian
Published:
journal of Iranian Public Administration Studies, Volume:7 Issue: 2, 2025
Pages:
111 to 147
https://www.magiran.com/p2821494  
سامانه نویسندگان
  • Reza Vaezi
    Author (2)
    Full Professor public administration, Allameh Tabataba'i University, Tehran, Iran
    Vaezi، Reza
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