Intelligent and Innovative Approaches to Delivering Social Welfare Schemes in India: Leveraging Artificial Intelligence for Public Impact

Artificial Intelligence (AI) adoption is growing rapidly across sectors, yet significant barriers hinder its acceptance in Indian government social welfare schemes. This research investigates factors influencing AI adoption using a mixed-methods approach, including the Delphi method with 13 experts and a survey of 146 respondents. The study identifies five key themes from a systematic literature review: social environment, organizational issues, technology-related issues, technology ecosystem, and individual factors. Concerns highlighted include data privacy, security vulnerabilities, trust in AI’s transparency, and a perceived lack of accountability in AI decision-making amongst others.Despite these concerns, the study reveals areas where respondents are comfortable using AI, particularly in healthcare, finance, and customer service sectors, suggesting a conditional acceptance based on context. The findings emphasize that addressing both technological and human factors— such as trust, security, and transparency is critical for fostering AI acceptance in Social Welfare schemes by Governments in India.By addressing these barriers and leveraging areas of comfort, policymakers can promote AI integration in social welfare schemes. This research contributes to existing literature by offering insights into user perceptions, with implications for theory, practice, and policy. Future research should focus on longitudinal studies to track shifts in public attitudes as AI technologies evolve.