Artificial Intelligence in Public Administration: Opportunities, Challenges, and Policy Implications for India
Abstract
Artificial Intelligence (AI) is increasingly transforming the functioning of governments by enabling data-driven decision-making, improving public service delivery, and enhancing administrative efficiency. In India, where governance involves managing a vast population, diverse socio-economic conditions, and complex administrative challenges, AI presents significant opportunities for improving the quality and accessibility of public services. The integration of AI into public administration can support predictive governance, automate routine administrative processes, strengthen policy implementation, and enable more responsive governance systems.
However, the adoption of AI in public administration also raises important concerns related to data privacy, algorithmic bias, transparency, accountability, and digital inequality. The effectiveness of AI-driven governance depends not only on technological advancement but also on ethical frameworks, institutional capacity, and inclusive policy approaches. Developing countries like India face additional challenges due to differences in digital infrastructure, administrative readiness, and public awareness.
This paper examines the role of Artificial Intelligence in Indian public administration by analysing its potential benefits, emerging challenges, and policy implications. It argues that AI should be viewed as a supportive tool that enhances human administrative capabilities rather than replacing human decision-making. The paper highlights the need for responsible AI governance, capacity building among public officials, stronger regulatory mechanisms, and citizen-centric approaches to ensure that AI contributes to transparent, efficient, and inclusive governance.
How to Cite This Article
Laxmi (2026). Artificial Intelligence in Public Administration: Opportunities, Challenges, and Policy Implications for India . Journal of Frontiers in Multidisciplinary Research (JFMR), 7(2), 35-40. DOI: https://doi.org/10.54660/.JFMR.2026.7.2.35-40