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The gathering brought together senior executives from global technology firms, domestic start-ups, academic leaders and policymakers, signalling a concerted push by New Delhi to position the country as both a major market and a development hub for AI. Modi framed the technology as central to economic growth, public service delivery and national competitiveness, arguing that India’s digital public infrastructure and vast talent pool provide a foundation for leadership in the field.

Speaking at the event, Modi said AI must be “inclusive and responsible”, emphasising applications in healthcare, agriculture, education and governance. He pointed to platforms such as Aadhaar, the Unified Payments Interface and the CoWIN vaccination system as examples of large-scale digital architecture that could integrate advanced analytics and machine learning.

The summit’s optics were carefully managed to reflect global engagement. Executives from leading US technology companies shared stages with founders of domestic firms working on generative AI models, language tools and enterprise software. Representatives from multilateral bodies and research institutions discussed governance frameworks, data protection and the need for cross-border collaboration.

Yet the conference also exposed tensions between ambition and execution. Several sessions ran behind schedule, and some industry participants privately expressed concern over policy uncertainty, particularly around data localisation, cross-border data flows and regulatory oversight. Draft frameworks on AI ethics and safety remain under consultation, and companies are awaiting clarity on compliance requirements.

The event unfolded against a backdrop of intensifying global competition. The United States continues to dominate foundational AI research and chip design, while China has invested heavily in domestic models and semiconductor capacity. The European Union has advanced comprehensive legislation through its AI Act, seeking to set global standards on risk and accountability.

India’s approach has been more incremental. The Ministry of Electronics and Information Technology has outlined plans to support compute infrastructure, encourage domestic large language models and expand skilling initiatives. Budget allocations for semiconductor manufacturing and design-linked incentives aim to reduce dependence on imports, although fabrication plants remain years away from full-scale production.

Industry analysts note that India’s strength lies in its software services sector and a large base of engineers. According to data from industry bodies, the country produces hundreds of thousands of engineering graduates annually, many of whom work in IT and business process outsourcing. Major domestic firms have announced internal AI integration plans, embedding generative tools into consulting, customer support and software development workflows.

At the same time, structural constraints are evident. High-performance computing resources are limited compared with those available in the US and China, and advanced chips are largely imported. Electricity reliability, data centre capacity and high-speed connectivity vary across regions. Venture capital funding for deep-tech ventures has fluctuated amid global market volatility.

Civil society groups and some academics used the summit to call for stronger safeguards. They warned that rapid deployment of AI systems without robust oversight could exacerbate misinformation, bias and privacy violations. India’s data protection law, enacted last year, sets out obligations for companies handling personal data, but implementing rules and enforcement mechanisms are still being developed.

Opposition figures have questioned whether headline events translate into durable policy outcomes. They argue that sustained investment in research universities, independent regulators and judicial capacity will be essential to manage the societal impact of AI. Some economists have also cautioned that automation could disrupt segments of the services workforce, requiring targeted reskilling programmes.

Global investors, however, continue to view India as a growth market. International cloud providers have expanded data centre footprints in cities such as Mumbai, Hyderabad and Chennai. Partnerships between domestic start-ups and multinational firms aim to build AI systems tailored to local languages and contexts, addressing a market of more than a billion people with diverse linguistic needs.

Modi’s messaging emphasised sovereignty alongside collaboration. He has repeatedly advocated for a global framework on AI governance that reflects the priorities of emerging economies, not solely those of advanced industrial nations. At the summit, he called for shared principles that balance innovation with ethical safeguards, while ensuring access for developing countries.

Diplomatically, the conference reinforced India’s profile as a convening power in technology policy, following its presidency of the G20 and engagement in forums on digital public goods. Whether that translates into tangible influence over global AI standards will depend on sustained coordination with like-minded partners and domestic regulatory coherence.

The twin agreements signal a coordinated push to deepen collaboration on artificial intelligence research, semiconductor supply chains and standards-setting at a time when global competition over emerging technologies is intensifying. Officials described the move as part of a broader effort to align trusted partners around open, secure and innovation-driven AI ecosystems.

The Pax Silica Initiative, framed as a platform for cooperation among governments, industry and research institutions, aims to promote responsible AI development anchored in democratic values and transparent governance. By endorsing the declaration, India has committed to work with other signatories on areas including AI safety frameworks, interoperability standards and resilient semiconductor networks. The initiative also seeks to reduce vulnerabilities in critical technology supply chains, particularly in advanced chips that underpin AI systems.

The Joint Statement on the India–U. S. AI Opportunity Partnership outlines specific areas of collaboration between New Delhi and Washington. According to officials familiar with the discussions, the partnership will prioritise joint research projects, exchanges between academic institutions and closer engagement between start-ups and venture capital ecosystems in both countries. It also envisages cooperation on workforce development, with a focus on skilling programmes to meet rising demand for AI engineers, data scientists and semiconductor specialists.

Senior representatives from both sides emphasised that the agreements build on an expanding technology agenda that has gathered pace over the past two years. The United States has identified India as a key partner in diversifying supply chains for critical technologies, while New Delhi has sought greater access to advanced know-how and investment to support its domestic manufacturing ambitions.

The semiconductor dimension is central to the Pax Silica framework. Global shortages during the pandemic exposed structural weaknesses in chip production networks, prompting governments to reassess their dependence on a limited number of manufacturing hubs. India has since launched incentive schemes to attract chipmakers and component suppliers, positioning itself as a complementary node in the global value chain. Closer coordination with U. S. firms and research laboratories is expected to support technology transfer and design capabilities.

Artificial intelligence governance is another pillar of the collaboration. Policymakers in New Delhi have been working on a regulatory architecture that balances innovation with safeguards against misuse. The partnership with the United States is expected to facilitate dialogue on standards, testing protocols and ethical guidelines. Both countries have expressed support for international cooperation to ensure AI systems are transparent, accountable and aligned with human rights principles.

Industry leaders present at the summit pointed to the commercial opportunities arising from deeper integration. India’s digital economy has expanded rapidly, driven by widespread smartphone adoption and a thriving start-up ecosystem. U. S. technology companies view the market as both a testing ground for scalable AI applications and a source of skilled talent. Joint ventures and research collaborations are likely to accelerate as policy barriers are addressed.

Analysts say the agreements also carry geopolitical significance. As rival powers invest heavily in AI and semiconductor capabilities, technology has become intertwined with national security and economic resilience. By formalising cooperation through the Pax Silica Declaration and the AI Opportunity Partnership, New Delhi and Washington are signalling intent to shape global norms rather than react to them.

The AI Impact Summit in New Delhi brought together policymakers, technologists and academics from multiple countries, underscoring the growing prominence of the city as a convening platform for debates on digital governance. Discussions ranged from generative AI applications in healthcare and education to concerns over misinformation and algorithmic bias. The signing of the declaration and joint statement provided a tangible outcome to those deliberations.

Officials indicated that working groups would be established to translate the commitments into concrete projects, with timelines and measurable targets to be announced in due course. Engagement with private sector stakeholders and research universities is expected to be formalised through memoranda of understanding and funding calls.

Singapore’s drive to harness artificial intelligence as an engine of economic growth is entering a decisive phase marked by abundant ambition and clear signs of strain across company ranks. Government fiscal policy and private-sector deployment are converging on AI, but weak data infrastructure, skills gaps and uneven returns are tempering expectations even as enterprises escalate investments and policy support grows.

Last week, the nation’s Budget for the 2026 fiscal year unveiled a suite of measures aimed at elevating AI adoption across multiple industries. Prime Minister and Finance Minister Lawrence Wong confirmed the establishment of a National AI Council, to be chaired by himself, tasked with coordinating research, regulation and investment to align public and private interests in developing AI capability. The plan also includes National AI Missions focused on advanced manufacturing, connectivity and logistics, finance and healthcare, sectoral areas where government and business leaders see the most potential for productivity gains and value creation. The budget expands fiscal incentives with enhanced tax deductions for AI-related expenditures over the next two assessment years and widened grant schemes to support adoption, workforce training and enterprise transformation. Leaders of major consultancies said these measures signal a shift from experimentation to enterprise-scale adoption and give firms a clearer pathway to embed AI into core operations.

Despite this policy momentum, data from industry surveys and corporate research paint a more nuanced picture of utilisation and outcomes. Adoption of AI tools in Singapore is now near universal among larger firms, with about 96 per cent reporting some level of use. But a significant gap remains between deployment and measurable returns on investment. Only a minority of organisations consider themselves leaders in achieving strong, sustained ROI, indicating an emerging disconnect between AI deployment at scale and operational readiness to turn it into business value. Executives widely acknowledge that sprawling and complex data environments, coupled with cybersecurity concerns, are contributing to operational friction and risks that constrain potential gains.

Private forecasts and vendor research suggest that enterprises are committed to accelerating AI spending even as returns lag. Surveys of business leaders show average investments in AI of around SG$18.9 million, with expectations for investment growth of roughly 38 per cent over the next two years and ROI projections rising to an average of 29 per cent during the same period. Yet analysts note that these returns will depend significantly on firms’ ability to bridge gaps in data readiness and workforce capability. Many Singapore companies acknowledge limited internal training, fragmented data integration and widespread informal use of ungoverned AI tools, all of which undermine robust enterprise-level strategy and governance structures.

Structural issues are as salient as technical ones. Industry leaders point to weaknesses in reliable data foundations and the need for stronger leadership alignment to embed AI into strategic operations rather than relegated to pilot projects or isolated business functions. Senior executives contend that competitive advantage over the coming decade will be determined less by technology choice and more by how effectively organisations build hybrid human-AI teams and integrate AI into everyday workflows.

Talent acquisition and retention also feature prominently in conversations around Singapore’s AI trajectory. Advanced AI, cloud and cybersecurity skills are in high demand globally and Singapore is no exception, with firms reporting difficulty scaling teams with the specialised expertise needed to support complex AI systems. This talent shortage both drives up costs and slows the pace at which organisations can absorb and leverage new technologies.

Cloud infrastructure and advanced digital foundations are another determinant of success. Financial services institutions in Singapore, for example, are among the most advanced globally in cloud adoption, with a majority running core workloads in cloud or hybrid environments that facilitate large-scale AI deployment. This infrastructure supports use cases ranging from compliance and risk management to fraud detection and transaction monitoring. However, budget constraints, talent gaps and integration challenges remain headwinds even in these relatively strong pockets of adoption.

Commentators outside the corporate sphere emphasize the importance of inclusive growth, noting that small- and medium-sized enterprises must not be left behind in the national AI push. Business federation and consultancy leaders warn that without targeted support for smaller firms to sustain, not just adopt, AI technologies, widening capability divides could undermine broader economic innovation and productivity goals.

This milestone reflects not just a vast user base but also a distinct pattern of adoption: students in India now represent the largest single demographic of ChatGPT users worldwide, according to Altman, who highlighted the role younger generations are playing in embedding generative AI into daily workflows for learning and productivity.

The 100 million figure forms a significant share of ChatGPT’s global weekly active user count, which stood at about 800 million as of October 2025 and is widely projected to edge closer to 900 million as platforms refine their offerings and expand reach. OpenAI’s decision to open an office in New Delhi in August 2025 and tailor pricing, including a lower-cost subscription tier later made free for a year, is seen as part of a strategy to deepen engagement in what many technology firms regard as a key growth market.

Altman underscored India’s demographic advantages, including a population exceeding one billion internet users and a large proportion of English speakers outside native English-speaking countries — factors that have made the country fertile ground for generative AI adoption. Many students have turned to ChatGPT for support with research, coding, examination preparation and language practice, reflecting a broader trend of digital tools being woven into educational routines.

Despite this surge, translating sheer user numbers into sustained economic returns poses challenges for AI firms. India’s price-sensitive market and uneven internet access complicate monetisation, causing some companies to adjust their strategies to balance affordability with revenue generation. OpenAI’s tailored pricing and promotional offers have helped lower entry barriers, but broader monetisation across emerging markets may require further innovation in business models.

The competitive landscape in India’s AI space is intensifying. Alphabet’s Google has made inroads with its Gemini AI suite, aggressively targeting younger users through free one-year subscriptions and partnerships with telecom firms to broaden adoption among students and professionals. These efforts are part of a broader contest among technology giants to capture share in a market that has vast potential due to its size and digital engagement.

The presence of global tech leaders and politicians at the New Delhi summit highlights the geopolitical and economic significance of India’s AI trajectory. Policy discussions span topics from responsible AI governance and equitable access to scaling infrastructure and boosting domestic innovation capacity. Indian policymakers, alongside industry executives, are advocating approaches that leverage technology to enhance education, public services and economic participation, while grappling with concerns over job displacement and digital divides.

Altman has outlined priorities for fostering inclusive AI growth in India, emphasising the need for practical digital literacy, robust computing infrastructure and frameworks that ensure ethical deployment. Such an approach, he argues, will empower users to harness AI’s potential effectively rather than just expanding access to tools.

The prominence of India’s student base on ChatGPT has broader implications for how AI products are developed and tailored. Feedback from a large and diverse user community helps shape feature enhancements and localisation efforts, influencing global development roadmaps. For companies like OpenAI, this dynamic underscores a strategic shift from traditional markets in Europe and North America toward regions where usage patterns reflect unique demographic and cultural needs.

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