As technology becomes more deeply woven into corporate operations, the urgent need for ´digital governance´ has emerged. This encompasses both harnessing technology within governance frameworks and proactively addressing the novel risks it introduces. In their recent working paper, Akshaya Kamalnath and Lin Lin spotlight how China and India respond to these challenges, with a focus on both legal regulation and real-world corporate practices, informed by an empirical survey approach.
The analysis foregrounds China and India as essential, yet often overlooked, players in the global Artificial Intelligence landscape, contrasting their trajectories against those in the United States and European Union. The authors pose three central questions: how each country regulates Artificial Intelligence and data protection within corporate governance; the extent to which firms disclose and incorporate technical expertise into leadership structures; and how institutional and developmental realities influence national approaches to technology-related risks and innovation. Their findings highlight a broad convergence in corporate governance practices on Artificial Intelligence risks, although the underlying legal architectures differ. In China, robust regulatory activity and court engagement outpace India, whose regulatory development remains in earlier stages. However, the practical tools—specialist tech officers, board committees for technology risks, and public disclosures—are strikingly similar, shaped in China by state-led guidance and in India by market dynamics.
Delving deeper, the regulatory philosophies diverge. China emphasizes a state-driven, innovation-focused approach that utilizes soft-law instruments (guidelines, strategic plans) over stringent legal mandates, balancing risk management with encouragement of technological advancement. Its civil law tradition results in codified, prescriptive frameworks, especially for data protection and cybersecurity. India, in contrast, leans toward a principles-driven, common law model—more flexible, reliant on court interpretation and self-regulation—partially reflecting a slightly later adoption curve for Artificial Intelligence technologies. Policy in both countries encourages public sector leadership in Artificial Intelligence deployment, with China’s state-owned enterprises driving ESG-focused initiatives and India’s government agencies aspiring for social Artificial Intelligence tools. The experiences of both countries challenge the EU-US binary in regulatory narratives and offer valuable reference points for other emerging economies seeking to balance innovation and governance in the age of Artificial Intelligence.
