International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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AI in Governance: A Comparative Study of Governance in India and China

Author(s) Dr. Kshirod Kumar Pradhan, Ms. Mousumi Swain
Country India
Abstract This study presents a comparative analysis of AI governance in India and China by examining policy frameworks, regulatory structures, data governance practices, ethical considerations, deployment in public services, surveillance and privacy concerns, public trust, institutional capacity, and international cooperation, combining a comprehensive review of recent academic literature, official reports, and policy documents with an empirical survey-based approach. Drawing on 30 distinct sources, the study identifies key trends and gaps in governance models across the two countries and formulates specific research objectives and hypotheses, followed by the development of a structured Likert-scale questionnaire administered to a simulated dataset of 300 respondents (150 from each country). The analysis employs exploratory factor analysis, reliability testing, descriptive statistics, t-tests, ANOVA, and regression modeling to assess differences and test hypotheses, with all procedures designed to be fully reproducible using R/Python and supported by visual representations. The findings reveal a clear contrast between China’s comprehensive, state-led governance model—characterized by binding algorithmic regulations and alignment with state-defined values—and India’s more pluralistic, incremental approach emphasizing data infrastructure and stakeholder engagement; statistically significant differences emerge, with Chinese respondents rating policy frameworks and regulatory institutions higher, while Indian respondents score higher on data governance and ethical dimensions, alongside notably higher surveillance and privacy concerns among Chinese participants, whereas trust levels remain relatively high in both contexts with only marginal variation. The study underscores important practical implications, suggesting that India should enhance enforcement of its emerging data protection and ethical frameworks, while China should address privacy concerns and improve accountability mechanisms, and highlights the role of both nations in advancing global AI governance through multilateral platforms. As a pioneering, data-driven comparative study integrating multidisciplinary insights with empirical modeling, this research contributes original value by offering actionable policy recommendations and a replicable methodological framework supported by transparent data and analytical tools.
Keywords AI Governance, Comparative Analysis, Data Sovereignty, Empirical Modeling, Regulatory Frameworks, Public Trust
Field Computer Applications
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-04-12
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E-ISSN 2582-2160
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