Navigating barriers to GenAI adoption in public administration: A systematic evaluation and policy roadmap

Public administration serves as a crucial pillar of governance, ensuring efficient policy implementation, resource management, and service delivery. However, administrative processes often face challenges such as inefficiencies, resource constraints, and bureaucratic delays. The emergence of Generative Artificial Intelligence (GenAI) presents an opportunity to enhance decision making, optimize administrative workflows, and improve public service efficiency. Despite its potential, the widespread adoption of GenAI in public administration is prevented by various barrier, thus a systematic assessment and prioritizing is necessary to facilitate structured implementation. This study aims to identify, analyze, and categorize key barriers to GenAI adoption. It begins with a comprehensive literature review to identify potential barriers. Utilizing the Technology-Organization-Environment (TOE) framework, the study systematically classifies these barriers and employs the Fuzzy Best-Worst Method (FBWM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) to prioritize them based on their significance, causal influence and interdependencies. The novelty of this study lies in its structured segmentation of barriers offering a comprehensive understanding of the challenges impeding GenAI adoption. The study presents a GenAI use case in India, highlighting its practical application in one of the world's largest administrative ecosystems. Given India's complex governance structure, addressing these barriers provides a scalable model for Artificial Intelligence (AI) driven administration globally. Additionally, study proposes time bound policy recommendations for the systematic integration of GenAI in public administration, ensuring accountability and ethical compliance. This research also contributes to academic discourse and policy formulation, emphasizing the need for continuous AI policy assessment to keep pace with technological advancements and evolving governance structures.