China and India adopt contrasting approaches to AI governance
A new study compares how China and India are addressing AI governance, highlighting differences in regulatory models, corporate practices, and institutional traditions.

As AI becomes central to business strategy, questions of corporate governance and regulation are gaining prominence. The study by Akshaya Kamalnath and Lin Lin examines how China and India are addressing these issues through law, policy, and corporate practice.
The paper focuses on three questions: how regulations are shaping AI and data protection in corporate governance, how companies are embedding technological expertise into governance structures, and how institutional differences influence each country’s response.
Findings suggest a degree of convergence in governance practices. Both countries have seen companies create chief technology officer roles, establish committees to manage technological risks, and disclose information about their use of AI.
In China, these measures are largely guided by central and provincial authorities, while in India, they reflect market-driven demand.
China’s approach is characterised by a state-led model that combines laws, regulations, and soft-law tools such as guidelines and strategic plans. The system is designed to encourage innovation while addressing risks in an adaptive manner.
India, by contrast, has fewer binding regulations and relies on a more flexible, principles-based model shaped by judicial interpretation and self-regulation.
Broader themes also emerge. In China, state-owned enterprises are using AI to support environmental, social, and governance (ESG) goals, while India has framed its AI strategy under the principle of ‘AI for All’ with a focus on the role of public sector organisations.
Together, these approaches underline how national traditions and developmental priorities are shaping AI governance in two of the world’s largest economies.
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