India Pushes Inclusive AI Vision Amid US–China Tech Rivalry

At a time when artificial intelligence is increasingly shaped by the strategic rivalry between the United States and China, India is advancing a distinct proposition: AI must be inclusive, democratic, and accessible to the Global South. This was the central theme at the AI Impact Summit 2026 in New Delhi, where policymakers, technology leaders, and global stakeholders gathered to deliberate on the future of AI governance.

Prime Minister Narendra Modi set the tone with the Sanskrit phrase “Sarvajan Hitaya, Sarvajan Sukhaya”—for the welfare and happiness of all—underscoring that artificial intelligence should not become the preserve of a handful of corporations or powerful nations.

India’s articulation of an alternative vision reflects a broader concern among many countries about the concentration of AI development in hubs such as Silicon Valley and major Chinese tech centres. While the US and China currently dominate foundation models, computing infrastructure, and investment flows, much of the world risks remaining consumers rather than creators in the AI ecosystem.

A Meeting of Global Tech Leadership

Despite logistical and security challenges, the summit drew a formidable line-up of global technology leaders, including Sam Altman, Dario Amodei, and Demis Hassabis, alongside industry figures such as Cristiano Amon and Brad Smith.

India’s deep integration into the global technology ecosystem was also evident, with Indian-origin leaders heading several multinational firms, including Sundar Pichai.

The summit further highlighted ambitious investment plans. Industrial leaders such as Mukesh Ambani signalled substantial commitments towards building AI infrastructure, indicating India’s intent to develop domestic capabilities rather than rely solely on imported technologies.

Fear of AI Dependence

Underlying India’s push is a growing concern over technological dependence. As AI becomes embedded in critical sectors—healthcare, finance, defence, and governance—reliance on foreign-developed systems poses strategic and economic risks.

Echoing this sentiment, António Guterres warned that AI governance cannot be left to “a handful of countries or billionaires,” emphasising the need for global guardrails, transparency, and accountability.

India appears to be pursuing a dual-track strategy. First, it is fostering indigenous AI development tailored to its linguistic and cultural diversity. Start-ups such as Sarvam AI are working on large language models optimised for Indian contexts. Second, it aims to leverage its vast IT services ecosystem led by firms like Tata Consultancy Services and Infosys to deliver AI solutions globally.

Yet, questions remain about whether these efforts can match the scale and capital strength of US-based players like OpenAI and Anthropic, or China’s rapidly advancing platforms such as DeepSeek.

Open Source vs Concentrated Power

A recurring theme at the summit was the role of open-source AI. Arthur Mensch advocated for open models that can be adapted by nations seeking digital sovereignty without dependence on proprietary ecosystems.

Chinese AI offerings—often open-source and cost-effective—align in part with India’s accessibility goals. However, geopolitical tensions between the two countries have constrained collaboration. Since 2020, India has banned several Chinese applications on security grounds, limiting the scope for deeper technological engagement.

Meanwhile, US firms continue to hold a significant advantage in computing infrastructure and research investment. Evolving US policy frameworks on AI could further complicate efforts to establish the multilateral governance model championed by the United Nations.

A Middle Power’s Balancing Act

India’s position reflects the broader dilemma faced by middle powers in a bipolar technological order. The objective is clear: to remain independent without isolation, and collaborative without dependence. At its core, India’s ambition is to ensure that AI development reflects diverse voices, languages, and societal needs.

Whether this approach translates into leadership remains uncertain. Building foundational AI models demands enormous capital, advanced semiconductor access, and cutting-edge research infrastructure areas where the US and China maintain a decisive edge.

The summit in New Delhi was as much about signalling intent as it was about shaping outcomes. By convening global leaders and championing inclusive AI, India has positioned itself as an advocate for a more equitable technological future.

Yet ambition alone will not rebalance global power structures. The dominance of US and Chinese AI ecosystems remains formidable. India’s path may lie in leveraging its innovation capabilities and IT services strength to build applications atop global models, while gradually developing its own.