Navigating the AI Duopoly: India’s Quest for Digital Sovereignty and Algorithmic Governance in a US–China Dominated Global Order..
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Abstract
Capability in advanced artificial intelligence (AI) has been centralized in the United States and China(Leech et al., 2024), creating an extremely uneven distribution of power across the globe, which is just as important as a country's military or economic power in determining its political agency, with access to foundational models, semiconductor supply chains, and large-scale training data serving as a key determinant. The problem is not just a technical one for states outside the duopoly, but one of sovereignty. This paper explores the unique trajectory being taken by the world's most populous democracy and its rapidly growing digital economy in the face of an increasingly polarized AI landscape. The study, which uses qualitative policy analysis tools, suggests that structurally India is strong enough to stop being subjugated by technology but not robust enough to be algorithmically self-sufficient, given the current state of its governance structures, from 2018's National Strategy for Artificial Intelligence to the IndiaAI Mission(Chahal et al., 2021) and the India AI Governance Guidelines written in November 2025. The Indian approach to diplomacy, exemplified at the India AI Impact Summit in February 2026 in New Delhi, is an intentional shift in the global discussion of AI governance to put development equity and human-centric priorities at the heart of the discussion. India's principled non-alignment, thus, manifests in a digital manner, by involving both Washington and Beijing simultaneously while advancing a third path alternative for the Global South. However, significant issues are still not resolved: there is a significant leaning towards voluntary corporate compliance, foundational model capacity is still developing and stated data-sovereignty aspirations do not easily fit with substantial reliance on the external cloud infrastructure. The paper argues that the trajectory of algorithmic governance is more a diplomatic negotiation than a policy stance in India and is as much a result of internal institutional fragmentation as it is of power dynamics with the outside world.....
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References
Aayog, N. (2018). National strategy for artificial intelligence #AIForAll. Government of India.
Agarwal, A., & Nene, M. J. (2026). A federated architecture for sector-led AI governance: lessons from India. Transforming Government People Process and Policy, 1–14. https://doi.org/10.1108/tg-09-2025-0310
Alam, M. (2025). Artificial Intelligence as the New Soft Power Frontier: India’s Ethical AI Diplomacy in the Global South. In Advances in intelligent systems research/Advances in Intelligent Systems Research (pp. 356–374). Atlantis Press. https://doi.org/10.2991/978-94-6463-950-6_24
Bansal, S., & Jain, N. (2023). A Comprehensive Study Assessing the Transformative Role of Artificial Intelligence in India’s Governance Policy Framework. International Journal for Research in Applied Science and Engineering Technology, 11(7), 1748–1756. https://doi.org/10.22214/ijraset.2023.54973
Beaumier, G., & Gjesvik, L. (2025). Digital Governance in a Rubber Band: Structural Constraints in Governing a Global Digital Economy. Global Studies Quarterly, 5(2). https://doi.org/10.1093/isagsq/ksaf043
Bradford, A. (2020). The Brussels Effect: How the European Union Rules the World. In eYLS (Yale Law School). Yale University. https://doi.org/10.1093/oso/9780190088583.001.0001
Bradford, A. (2023). Digital Empires. https://doi.org/10.1093/oso/9780197649268.001.0001
Bureau, P. I. [PIB]. (2025). India’s common compute capacity crosses 34,000 GPUs.
Carter, H., & Hermansen, A. (2026). AI for Economic and Social Good in India. https://doi.org/10.70828/blmf5264
Cave, S., & hÉigeartaigh, S. Ó. (2018). An AI Race for Strategic Advantage. 36–40. https://doi.org/10.1145/3278721.3278780
Chahal, H., Abdulla, S., Murdick, J., & Rahkovsky, I. (2021). Mapping India’s AI Potential. https://doi.org/10.51593/20200096
Choudhary, S., & George, C. A. (2025). India’s Dormant Attitude towards AI Regulations. Amicus Curiae, 6(3), 522–538. https://doi.org/10.14296/ac.v6i3.5783
Couture, S., & Toupin, S. (2019). What does the notion of “sovereignty” mean when referring to the digital? New Media & Society, 21(10), 2305–2322. https://doi.org/10.1177/1461444819865984
Floridi, L. (2020). The Fight for Digital Sovereignty: What It Is, and Why It Matters, Especially for the EU. Philosophy & Technology, 33(3), 369–378. https://doi.org/10.1007/s13347-020-00423-6
George, Dr. A. S., Dr.T.Baskar, & Dr.M.M.Karthikeyan. (2026). India’s M.A.N.A.V Vision: Redefining Global AI Governance Through Human-Centric Principles and Strategic Sovereignty. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.18730380
Goode, J. P. (2020). Artificial intelligence and the future of nationalism. Nations and Nationalism, 27(2), 363–376. https://doi.org/10.1111/nana.12684
Hall, I. (2016). Multialignment and Indian Foreign Policy under Narendra Modi. The Round Table, 105(3), 271–286. https://doi.org/10.1080/00358533.2016.1180760
Herald, D. (2025). India’s sovereign AI model will be ready by February: IT Ministry Secretary. Deccan Herald.
Hindu, T. (2025). Model conduct: On India, AI use. The Hindu.
Hogarth, I. (2018). AI nationalism.
Imbrie, A., Kania, E. B., & Laskai, L. (2020). The Question of Comparative Advantage in Artificial Intelligence: Enduring Strengths and Emerging Challenges for the United States. https://doi.org/10.51593/20190047
India, R. B. of. (2025). Framework for responsible and ethical enablement of artificial intelligence (FREE-AI): Report of the committee. Reserve Bank of India.
Leech, G., Garfinkel, S., Yagudin, M., Briand, A., & Zhuravlev, A. (2024). Ten Hard Problems in Artificial Intelligence We Must Get Right. In arXiv (Cornell University). Cornell University. https://doi.org/10.48550/arxiv.2402.04464
Malik, P., Jain, N., Kanwar, S., Das, B., & Dhadwal, S. (n.d.). AI Markets and Competition in India. In RePEc: Research Papers in Economics. Federal Reserve Bank of St. Louis.
MeitY, M. of E. and I. T. (2025). India AI governance guidelines. Government of India.
Mohan, C. R. (2015). Modi’s World: Expanding India’s Sphere of Influence. https://www.amazon.com/Modi-World-Extending-sphere-Influence/dp/9351772055
Mueller, M. (2019). Against Sovereignty in Cyberspace. International Studies Review, 22(4), 779–801. https://doi.org/10.1093/isr/viz044
Pohle, J., & Thiel, T. (2020). Digital sovereignty. Internet Policy Review, 9(4). https://doi.org/10.14763/2020.4.1532
Roberts, H., Cowls, J., Morley, J., Taddeo, M., Wang, V., & Floridi, L. (2021). The Chinese Approach to Artificial Intelligence: An Analysis of Policy, Ethics, and Regulation. In Philosophical studies series (pp. 47–79). Springer International Publishing. https://doi.org/10.1007/978-3-030-81907-1_5
Semaladhari, R. (2026). India AI Impact Summit 2026: A Defining Moment for Global AI Leadership. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.18763209
Standard, B. (2026). Why Sarvam’s new 105B model marks a shift in India’s sovereign AI ambitions. Business Standard.
Steinhoff, J. (2022). The Proletarianization of Data Science. In The MIT Press eBooks (pp. 191–206). The MIT Press. https://doi.org/10.7551/mitpress/13835.003.0015
Subrahmanyam, J. (2020). The India way strategies for an uncertain world.
Taeihagh, A. (2021). Governance of artificial intelligence. Policy and Society, 40(2), 137–157. https://doi.org/10.1080/14494035.2021.1928377
Ulnicane, I., Knight, W., Leach, T., Stahl, B. C., & Wanjiku, W.-G. (2020). Framing governance for a contested emerging technology:insights from AI policy. Policy and Society, 40(2), 158–177. https://doi.org/10.1080/14494035.2020.1855800
Xie, Y., & Avila, S. (2024). The Social Impact of Generative LLM-Based AI. In arXiv (Cornell University). Cornell University. https://doi.org/10.48550/arxiv.2410.21281.