Policy Networks in the Governance of Artificial Intelligence for Public Service Delivery: Evidence from Makassar City, Indonesia - Muh. Nasrullah; Muhammad Luthfi Siraj (Universitas Negeri Makassar, 2026)
The rapid advancement of Artificial Intelligence (AI) has accelerated the transformation of public service delivery toward more efficient, responsive, and data-driven systems. However, the successful implementation of AI in the public sector depends not only on technological readiness but also on the capacity of multiple stakeholders to establish collaborative policy networks. This study aims to analyze policy networks in the governance of AI utilization for public service delivery in Makassar City, Indonesia. A qualitative approach with a case study design was employed. Data were collected through in-depth interviews, observations, and document analysis involving local government officials, academics, technology companies, digital communities, and citizens as service users. Data were analyzed using the interactive model of Miles, Huberman, and Saldaña, guided by the Policy Network Theory framework. The findings reveal that AI governance in Makassar City is shaped by a collaborative network involving multiple actors with complementary roles and resources. The local government acts as the network coordinator, while private-sector organizations and academic institutions provide strategic resources, including technological expertise, knowledge, and innovation. Interdependence and resource exchange emerge as critical factors supporting AI implementation in public services. Nevertheless, AI governance continues to face challenges related to regulatory limitations, data integration, human resource capacity, and concerns regarding ethics and information security. This study highlights that strengthening collaborative and adaptive policy networks is a fundamental prerequisite for achieving effective and sustainable AI-driven public service delivery.