Designing AI-Driven Public Service Delivery Models for Citizen-Centered Decision Making

• Author(s): Kingsley Wisdom Akhibi
• Paper ID: 1713025
• Page: 1571-1585
• Published Date: 22-12-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 6 December-2025

Abstract

The rising adoption of artificial intelligence (AI) in the delivery of government services promises unprecedented efficiency, predictive, and responsiveness enhancements, but at the same time, a critical evaluation is warranted concerning transparency, justice, accountability, and citizen trust. This research explores how a systemic architecture for AI-enabled government service delivery can be developed to optimize government administration with a suite of ethics ensuring accountability, democratic participation, and alignment with civil society. The research applies a convergence of theoretical frameworks from Algorithmic State Architecture, Human-Centered AI, democratic participatory theory, Socio-Technical Systems Theory, and ethics literature on AI. Three high-priority sectors; Housing, Transport, Healthcare are considered for this research. The research uses a mixed research design that incorporates quantitative research on the efficiency enhancement potential of AI-based workflow optimization, together with qualitative findings from case studies, document analysis, interviews, and citizen surveys. The findings of this research work shows that AI enhances efficiency with predictive analytics, automated workflow, and decision support systems that provide proactive resource allocation, thereby minimizing service bottlenecks. Nonetheless, efficiency enhancement cannot remain enduringly stable, hence socially justified, in the presence of non-transparent AI mechanisms. The proposal of a multi-level Citizen-Centered AI-Driven Public Service Delivery Model is based on a convergence of data governance, algorithmic processing, human oversight, transparency, and accountability mechanisms, along with community engagement. The comparative analysis of different sectors indicates that participatory design approaches, in conjunction with ethics-oriented governance frameworks, are capable of increasing citizen trust, equity, and relevance, especially within the LPICs, where challenges with existing capacity continue. The research supports theory, practice, and application with a complementary concept structure, along with a set of policy guidelines on the responsible use of AI in the government sector, thus proving that AI enhances public service delivery systems, in addition to democratic governance practices, when implemented within the guidelines of a citizen-centered, transparent, and accountable structure.

Keywords

Artificial Intelligence in Public Services; Citizen-Centered AI; Algorithmic State Architecture; Participatory Governance; Ethical and Explainable AI; Algorithmic Accountability; AI-Driven Workflow Optimization; Public Sector Governance; Community Engagement; Responsible AI Adoption

Citations

IRE Journals:
Kingsley Wisdom Akhibi "Designing AI-Driven Public Service Delivery Models for Citizen-Centered Decision Making" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 1571-1585

IEEE:
Kingsley Wisdom Akhibi "Designing AI-Driven Public Service Delivery Models for Citizen-Centered Decision Making" Iconic Research And Engineering Journals, 9(6)