From Rule Taker to Rule Shaper: Examining India’s Emerging Role in Global AI Governance Through the Lens of Economic Statecraft

Introduction

International politics has always been about power, but what counts as power changes. For much of the twentieth century, influence in multilateral settings derived from military capability, economic weight and the diplomatic leverage that flowed from both. The twenty-first century has introduced a new and under-theorised variable: the capacity to govern emerging technologies credibly, at scale and in ways that other states find adaptable. Artificial Intelligence is perhaps the most consequential test of that proposition.

Governments across the world have responded to AI’s rise by rushing to develop regulatory frameworks, multilateral commitments and standards-setting initiatives. The OECD’s AI Principles,¹ UNESCO’s Recommendation on the Ethics of Artificial Intelligence² and the United Nations Global Digital Compact³ collectively mark significant steps forward. Yet the architecture that has emerged is fragmented, skewed towards the concerns of technologically advanced economies, and largely silent on the governance challenges most pressing for the global majority: digital infrastructure, institutional capacity, technology access and public-sector AI deployment.⁴

It is in this context that India’s position becomes worth examining seriously. India is not among the world’s leading developers of frontier AI models, and its research publication record in advanced machine learning lags behind that of the United States, China and several European countries.⁵ Yet since at least 2014, India has been building something arguably more consequential for governance purposes: a population-scale digital public infrastructure stack that now serves over a billion people, reaches into remote rural economies and has attracted interest from dozens of countries seeking workable models for digital state capacity. The Aadhaar biometric identity system, the Unified Payments Interface, CoWIN and, more recently, the ONDC open commerce network collectively constitute a digital governance ecosystem with few parallels globally.

This paper asks a straightforward question: does India’s domestic digital governance experience translate into international influence within the emerging architecture of AI governance, and if so, through what mechanisms? Answering that question requires moving beyond the existing literature’s preoccupation with frontier AI capability and regulatory competition. It calls for a framework that takes development seriously, not as an outcome to be achieved through good governance but as a resource that shapes what countries can credibly offer in international negotiations.

The paper makes two contributions towards that end. The first is conceptual: it introduces Development-Centred AI Diplomacy, a framework that reframes domestic digital governance capability as a source of international influence. The second is analytical: it proposes the RISE Framework, a four-pillar model linking Resources, Institutions, Strategic Coalitions and Entrepreneurial Leadership, as a structured account of how that influence is generated and sustained over time.

The paper proceeds as follows. The literature review situates the argument within debates on AI governance, economic statecraft and emerging-power agency. The methodology section explains the research design. The findings are presented across four subsections corresponding to the four pillars of the RISE Framework. The discussion develops the concept of Development-Centred AI Diplomacy and evaluates its theoretical implications. The conclusion draws out the policy and scholarly implications.

Literature review

A. AI governance and the fragmentation problem

The literature on global AI governance has grown substantially but remains concentrated around three clusters of concern. The first focuses on ethics and rights-based regulation, examining how principles of transparency, accountability and non-discrimination can be embedded into AI systems and the institutions that oversee them.⁶ The second addresses geopolitical competition, particularly the rivalry between the United States and China over AI standards, export controls and technological leadership.⁷ The third examines the institutional architecture of global AI governance, mapping the proliferating set of multilateral frameworks and their often-overlapping mandates.⁸

What links these three strands is an implicit assumption: that the actors most likely to shape global AI governance are those with the greatest technological capability or regulatory authority. The European Union matters because of the Brussels Effect.⁹ The United States matters because of its AI research leadership and its capacity to impose export controls. China matters because of the scale and ambition of its national AI strategy. Emerging economies appear in the literature primarily as objects of governance rather than subjects of it.

This is a significant gap. Several scholars have noted that the global AI governance landscape is not merely fragmented in institutional terms but also skewed in representational terms: the agendas of multilateral bodies reflect the concerns of technologically advanced states rather than the development priorities of the majority.¹⁰ But the literature has not yet developed adequate theoretical tools for understanding how countries outside the established technology powers might acquire meaningful governance influence.

B. Economic statecraft and governance as power

A more productive entry point comes from the literature on economic statecraft. Baldwin’s foundational account established that states regularly use economic instruments, including aid, trade policy and investment, to pursue political objectives.¹¹ More recently, Farrell and Newman showed that control over key nodes in global economic networks confers structural power: states positioned at the centre of financial or technological networks can use that position to coerce or constrain others.¹² Blackwill and Harris extended the analysis to geoeconomics, arguing that the weaponisation of economic interdependence has become a primary tool of great-power competition.¹³

What is less well theorised in this literature is the governance dimension. Economic statecraft typically refers to the use of economic instruments for strategic ends. But what about the use of governance capability itself as a strategic instrument? A state that can credibly demonstrate how to build a digital payment system serving a billion users, or how to manage biometric identity infrastructure across diverse populations, possesses something valuable that cannot simply be purchased: practical institutional knowledge that other states want and cannot easily replicate. This is a different kind of economic statecraft, one grounded not in market leverage but in governance credibility.

C. Emerging powers and norm entrepreneurship

International Relations scholarship on emerging powers provides a third theoretical resource. Constructivist scholars have long argued that states can acquire international influence by shaping norms and expectations rather than relying exclusively on material capabilities.¹⁴ Acharya’s work on the multiplex world order goes further, challenging the assumption that legitimate governance innovations originate exclusively in advanced Western economies and arguing that local institutional diversity is increasingly central to global norm development.¹⁵

Applied to AI governance, these insights suggest that a state can acquire influence by contributing credible governance practices that other states find workable and adaptable. The question is not only whether a country has the most advanced AI but whether it has governance practices and institutional experiences that help resolve the real challenges other countries face. India’s digital public infrastructure, built at scale under conditions of resource constraint and institutional complexity, may represent precisely such a resource.

Taken together, these three bodies of literature point towards a theoretical gap: the absence of a framework that integrates domestic governance capability, economic statecraft and norm entrepreneurship into a coherent account of how emerging economies acquire influence in technology governance. This paper proposes Development-Centred AI Diplomacy as an initial attempt to fill that gap.

Methodology

This paper adopts a qualitative case study design with process tracing as its primary analytical strategy. The case is India’s engagement with global AI governance from approximately 2014, the year that marks the beginning of India’s Digital India initiative and a significant shift in its approach to digital governance, through early 2025. Process tracing is appropriate because the central research question concerns mechanisms rather than correlations: the aim is not to establish that India has acquired influence in AI governance but to identify the causal pathways through which that influence has been generated.¹⁶

The analysis draws on three categories of evidence. The first comprises official policy documents from the Government of India, including the National Strategy for Artificial Intelligence¹⁷ and the IndiaAI Mission framework,¹⁸ as well as multilateral documents including G20 declarations, GPAI reports, and UNESCO and OECD framework documents. The second category encompasses secondary scholarly literature across AI governance, development studies and International Relations. The third includes institutional data on India’s participation in multilateral AI forums, its bilateral digital partnership agreements and the international deployment of its digital public infrastructure platforms.

Document analysis followed a structured coding framework organised around the four pillars of the RISE Framework, developed inductively during the research process. Each pillar was assessed for evidence of capability (what India has built or established), engagement (how that capability has been used in international settings) and recognition (whether other states or international bodies have acknowledged and engaged with that capability). The coding was iterative, with the framework itself refined through successive passes through the evidence.

The study’s primary limitation is its focus on a single case. The findings are developed inductively from the Indian experience and have not been tested systematically against comparable cases. The paper does not claim generalisability beyond suggesting theoretical implications that future comparative research should test. A second limitation is that assessing influence in multilateral settings is methodologically difficult: attributing policy outcomes to specific actors is inherently uncertain, and the paper is careful to distinguish between India’s participation in governance processes and its demonstrated influence over governance outcomes.

Findings: India’s AI governance engagement through the RISE Framework

A. Resources: building the domestic capability base

India’s capacity to participate meaningfully in global AI governance rests, at its foundation, on a decade of domestic digital infrastructure investment. This investment is distinctive in character. Unlike the AI strategies of the United States or China, which are organised primarily around frontier research and commercial application, India’s approach has integrated technological development with public-sector deployment and institutional capacity building.

The core of this infrastructure is the India Stack: an interlocking set of digital public goods built on open application programming interfaces and designed to be interoperable across government departments, financial institutions and private service providers. Table 1 summarises the principal components and their governance relevance.

Table 1: India’s digital public infrastructure ecosystem and AI governance relevance

Note. Author’s compilation based on the Ministry of Electronics and Information Technology (2024), G20 (2023) and World Bank (2024). UPI transaction data from the National Payments Corporation of India (2024).

These platforms were designed to solve domestic public administration problems rather than to position India in international governance debates. But they have produced a governance resource that turns out to have significant international relevance: demonstrated, large-scale evidence that open, interoperable digital infrastructure can support financial inclusion, reduce administrative friction and strengthen state capacity even under severe resource constraints.

The IndiaAI Mission, approved by the Cabinet on 7 March 2024 with an outlay of Rs 10,372 crore over five years, represents a deliberate effort to build on these foundations in the AI domain specifically.¹⁹ The Mission commits to establishing a compute infrastructure of 10,000 or more GPUs through public-private partnership and to developing indigenous large multimodal models through a dedicated AI Innovation Centre. Crucially, the Mission frames AI capacity not primarily as a market-building exercise but as a public governance challenge: AI applications across healthcare, agriculture, education and public administration are foregrounded alongside research and commercial development.

B. Institutions: coordination, credibility and regulatory maturation

Governance capability is not only a matter of infrastructure. It also requires institutional arrangements capable of coordinating that infrastructure across actors, aligning public and private interests and maintaining the accountability mechanisms that sustain public trust. India’s institutional landscape for AI governance is still maturing, but several elements have proved significant for its international engagement.

The Ministry of Electronics and Information Technology has served as the primary institutional anchor for India’s digital governance initiatives. NITI Aayog’s 2018 National Strategy for Artificial Intelligence established an early policy framework that was distinctive in its orientation towards public-sector use cases and social development outcomes rather than purely commercial AI applications. More recently, the emergence of AI governance guidelines in 2025 and the establishment of interministerial coordination mechanisms have strengthened India’s capacity to articulate consistent positions in international forums.

Institutional coordination remains a genuine challenge. India’s AI governance responsibilities are distributed across multiple ministries, regulatory agencies and research institutions without a single coordinating body with clear authority. This fragmentation creates difficulties when India seeks to negotiate multilateral commitments that require coordinated implementation across government departments. The contrast with the European Union, which has been able to negotiate and implement a comprehensive AI regulatory framework through existing supranational institutions, is instructive.

That said, India’s institutional trajectory matters as much as its current state. The establishment of a dedicated AI Mission with a multi-year budget commitment signals institutional seriousness. The development of Digital Personal Data Protection legislation and the creation of bodies responsible for AI ethics review suggest that India is building the accountability infrastructure that credible governance engagement requires.

C. Strategic coalitions: multilateral engagement and the G20 moment

The transformation of India’s domestic digital governance experience into international influence has depended critically on the construction of strategic coalitions: multilateral partnerships that provide forums for India to share its governance experience, build relationships with countries facing similar challenges and shape the agenda of international AI governance discussions.

The most significant such forum has been the G20. During India’s G20 Presidency in 2023, India placed Digital Public Infrastructure at the centre of the global development agenda in a way that no previous G20 host had attempted. The New Delhi Leaders’ Declaration explicitly endorsed DPI as a tool for inclusive digital transformation, called for international cooperation on DPI capacity building and established a framework for sharing digital governance knowledge across member economies.²⁰ This was not simply an expression of Indian digital pride. It was a deliberate attempt to reshape the terms of international digital governance discussions in ways that privileged the kind of governance experience India had accumulated over the kind it had not.

India’s participation in the Global Partnership on AI as a founding member has provided a second avenue for coalition building. GPAI’s working groups on data governance, the future of work and responsible AI have provided platforms for Indian technical and policy experts to contribute to international standard-setting discussions in ways that are formally equal to those of more technologically advanced member states.²¹

The Voice of Global South Summits, hosted by India in 2023 and 2024, represent a third dimension of India’s coalition-building strategy. These gatherings brought together developing country governments to discuss shared digital governance priorities and positioned India as a broker between the Global South and the established AI governance institutions dominated by advanced economies. This brokerage role is significant: it allows India to claim representational legitimacy in multilateral forums in a way that goes beyond its bilateral relationships with any individual partner.

D. Entrepreneurial leadership: agenda-setting and norm entrepreneurship

The fourth pillar of the RISE Framework captures something harder to measure but no less consequential: India’s capacity to shape the agenda of international AI governance discussions through active policy entrepreneurship rather than passive participation.

Finnemore and Sikkink’s concept of norm entrepreneurship describes how actors with strong ideas and organisational platforms can shift international norms by framing issues in new ways and building coalitions around those frames.²² India’s advocacy for Development-Centred AI governance, which places digital inclusion, public-sector capacity and technology cooperation alongside safety and regulation as core governance priorities, represents exactly this kind of norm entrepreneurship.

The clearest evidence of this comes from the G20 DPI framework. Before India’s presidency, DPI was a technical concept discussed primarily in development finance and digital economy circles. By the end of India’s G20 year, it had been elevated to the status of a global policy priority, endorsed by the leaders of the world’s largest economies. That shift did not happen automatically. It required sustained diplomatic preparation, technical advocacy and political leadership across multiple bilateral and multilateral channels.

India has also sought to shape the governance of specific AI domains through bilateral partnerships. The expansion of UPI connectivity to over eight countries by mid-2025, the India-Singapore PayNow linkage established in 2023 and the growing number of countries seeking to adapt India’s DPI architecture to their own contexts all represent forms of norm diffusion grounded in demonstrated governance practice rather than regulatory fiat.

Table 2: The RISE Framework and India’s AI diplomacy architecture

Note. Author’s framework, drawing on the Ministry of Electronics and Information Technology (2024), G20 (2023), GPAI (2023) and Stanford University (2025).

Discussion

A. Development-Centred AI Diplomacy: theoretical implications

The findings reported above invite a retheorisation of the relationship between domestic governance and international influence in the context of emerging technology. The existing literature frames this relationship in two main ways. The first, associated with the Brussels Effect, holds that regulatory authority is the primary source of governance influence: states whose rules other states must follow in order to access their markets acquire the power to shape international standards.²³ The second, associated with technological competition, holds that AI research leadership and compute capacity determine who sets the governance agenda.

India’s trajectory does not fit comfortably into either framework. It lacks the market leverage of the European Union and the research capability of the United States or China. Yet it has demonstrably shaped the agenda of international AI governance discussions, particularly around DPI, digital inclusion and development-oriented AI applications. How?

The concept of Development-Centred AI Diplomacy offers one answer. Rather than competing on the terrain of regulation or frontier research, India has leveraged what it actually has: a population-scale digital governance track record that other developing countries want to understand and, in many cases, replicate. This track record functions not as market leverage but as credibility currency: it grants India standing to speak on governance questions that its technological capability alone would not justify.

This has broader theoretical implications. It suggests that the sources of governance influence in the AI era are more diverse than the existing literature implies. Technological capability and regulatory authority are real forms of power. But so is the capacity to demonstrate credible, adaptable, development-oriented governance practices at scale. States that can do this, even without possessing frontier AI capability, may acquire meaningful influence in multilateral governance settings, particularly as those settings increasingly grapple with questions of digital inclusion and institutional capacity rather than exclusively with safety regulation and frontier AI risks.

B. The limits and risks of India’s approach

The argument advanced here should not be mistaken for an optimistic account of India’s global AI governance trajectory. Several significant constraints and risks bear acknowledgement.

First, the gap between India’s digital governance ambitions and its frontier AI capabilities is real and consequential. As AI governance increasingly engages questions of advanced model development, compute access and semiconductor supply chains, India’s relative weakness in these areas limits the depth of its participation. Development-Centred AI Diplomacy is a genuine source of influence, but it is not a substitute for technological capability in every governance domain.

Second, the translation of domestic governance success into international influence depends on continued progress at home. India’s DPI platforms have faced genuine challenges, including implementation gaps, exclusion errors in Aadhaar and questions about data protection that remain only partially resolved. If domestic performance deteriorates or international interlocutors become more sceptical about the governance model India is promoting, the credibility that underlies Development-Centred AI Diplomacy will erode.

Third, the multilateral terrain is not neutral. The established AI powers have structural advantages in international governance that derive from their positions in global financial networks, their bilateral influence over developing countries and their capacity to set technical standards through industry consortia and standards bodies that India participates in only partially. India’s coalition-building strategy is necessary but not sufficient: it depends on sustained diplomatic engagement that has historically been difficult to maintain across different government administrations with varying foreign policy priorities.

Conclusion

This paper set out to examine whether and how India’s domestic digital governance experience translates into international influence within the emerging architecture of global AI governance. The findings, developed through process tracing and document analysis across the RISE Framework’s four pillars, suggest a qualified but meaningful affirmative answer.

India has leveraged its digital public infrastructure experience to shape multilateral agendas, build coalitions with developing country partners and establish itself as a credible voice on governance questions related to digital inclusion, interoperability and development-oriented AI. This influence has been most visible in the G20 DPI framework, the Voice of Global South initiatives and the expanding bilateral digital partnerships through which Indian governance models are being adapted by other states. It is less visible, and less established, in domains more directly concerned with frontier AI safety and advanced model regulation.

The concept of Development-Centred AI Diplomacy, introduced in this paper, offers a framework for understanding this pattern. It reframes domestic governance capability as a resource for international norm engagement rather than merely as an outcome to be achieved through global cooperation. The RISE Framework provides a structured model for assessing where a state’s governance diplomacy is strong and where it remains vulnerable.

For scholarship, the paper suggests that the study of global AI governance has been too narrowly focused on the established technology powers and the regulatory frameworks they produce. A more complete picture requires attention to how emerging economies leverage development governance experience as a form of international agency. India is a particularly instructive case, but it is unlikely to be unique.

For policy, the findings suggest that India’s transition from rule-taker to rule-shaper in AI governance is neither inevitable nor impossible. It depends on sustained domestic investment in AI capability and institutional coordination, consistent multilateral engagement, and continued credibility in the governance practices India is promoting internationally. The path is narrower than enthusiastic commentary often suggests. It is also more viable than sceptical accounts assume.

The future of AI governance will not be determined solely by who builds the most powerful models. It will also be shaped by who contributes credible, workable solutions to the governance challenges that the majority of the world actually faces. That is an opening India has begun to exploit. Whether it sustains and deepens that opening over the coming decade remains the genuinely open question.

Acknowledgements

The authors thank the research team at the Development Policy Lab India for institutional support and colleagues in the Indian foreign policy and technology governance research communities whose work has informed the arguments developed here. The views expressed in this paper are those of the authors alone and do not represent the position of any institution or government body.

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Footnotes

1. Organisation for Economic Co-operation and Development, Recommendation of the Council on Artificial Intelligence, OECD/LEGAL/0449 (adopted 22 May 2019, revised 3 May 2024).

2. United Nations Educational, Scientific and Cultural Organization, Recommendation on the Ethics of Artificial Intelligence (2021).

3. United Nations, Global Digital Compact (Annex I to the Pact for the Future, UN Doc A/RES/79/1, 22 September 2024).

4. Anna Jobin, Marcello Ienca & Effy Vayena, The Global Landscape of AI Ethics Guidelines, 1 Nature Machine Intelligence 389 (2019); United Nations Development Programme, Human Development Report 2023/24: Breaking the Gridlock – Reimagining Cooperation in a Polarised World (2024).

5. Stanford University, Institute for Human-Centered Artificial Intelligence, Artificial Intelligence Index Report 2025 (2025).

6. Luciano Floridi & Josh Cowls, A Unified Framework of Five Principles for AI in Society, 1 Harv. Data Sci. Rev. (2019); Jobin, Ienca & Vayena, supra note 4.

7. Allan Dafoe, AI Governance: A Research Agenda (Future of Humanity Inst., Univ. of Oxford, 2018); Huw Roberts et al., The Chinese Approach to Artificial Intelligence: An Analysis of Policy, Ethics, and Regulation, 36 AI & Soc’y 59 (2021).

8. Peter Cihon, Standards for AI Governance: International Standards to Enable Global Coordination in AI Research and Development (Future of Humanity Inst., Univ. of Oxford, 2019); OECD, supra note 1.

9. Anu Bradford, The Brussels Effect: How the European Union Rules the World (2020).

10. United Nations Development Programme, supra note 4; World Bank, World Development Report 2024: The Middle-Income Trap (2024).

11. David A. Baldwin, Economic Statecraft (1985).

12. Henry Farrell & Abraham L. Newman, Weaponized Interdependence: How Global Economic Networks Shape State Coercion, 44 Int’l Security 42 (2019).

13. Robert D. Blackwill & Jennifer M. Harris, War by Other Means: Geoeconomics and Statecraft (2016).

14. Martha Finnemore & Kathryn Sikkink, International Norm Dynamics and Political Change, 52 Int’l Org. 887 (1998).

15. Amitav Acharya, The End of American World Order (2014); Amitav Acharya, Constructing Global Order: Agency and Change in World Politics (2018).

16. Alexander L. George & Andrew Bennett, Case Studies and Theory Development in the Social Sciences (2005).

17. NITI Aayog, National Strategy for Artificial Intelligence: #AIForAll (2018).

18. Ministry of Electronics and Information Technology, Government of India, IndiaAI Mission: Comprehensive Framework (2024).

19. Ministry of Electronics and Information Technology, Government of India, supra note 18 (Cabinet approval of the IndiaAI Mission, 7 March 2024, outlay of Rs 10,372 crore).

20. G20, G20 New Delhi Leaders’ Declaration (G20 India Presidency, 2023).

21. Global Partnership on Artificial Intelligence, GPAI Annual Report 2023 (GPAI Secretariat / OECD, 2023).

22. Finnemore & Sikkink, supra note 14.

23. Bradford, supra note 9.