India Influence Summit: New Delhi's Strategic Intent to Compete for Global AI Leadership

On February 20, the five-day India AI Impact Summit concluded in New Delhi, the capital of India. Nearly a hundred political leaders and technology executives attended the conference, including Indian Prime Minister Narendra Modi, French President Emmanuel Macron, UN Secretary-General António Guterres, Google CEO Sundar Pichai, and OpenAI CEO Sam Altman. This global AI summit, held in a developing country, extended its core agenda beyond mere technical discussions. The Modi administration is striving to position India as a key node in the global artificial intelligence ecosystem. The summit's slogan, "Designed in India, Delivered to the World," points to a clear strategic goal: to break the duopoly of China and the United States in cutting-edge AI fields and secure a leadership role for India in the Fourth Industrial Revolution.

India's Ambition: From "Talent Exporter" to "Rule Maker"

India's positioning of AI is not limited to technological catch-up. At the opening of the summit, Modi stated: We must democratize artificial intelligence. It must become a tool for inclusion and empowerment, especially for the Global South. This statement comes against the backdrop of India leveraging its experience in digital public infrastructure—including the Aadhaar digital identity system covering over 1.3 billion people and the Unified Payments Interface (UPI) handling hundreds of millions of transactions daily—as a model for promoting low-cost, large-scale AI solutions to developing countries. Officials from India's Ministry of Electronics and Information Technology revealed to the media that they aim to replicate the model of India Stack in the field of AI governance.

This ambition is supported by real-world data. India has nearly 1 billion internet users, making it one of the world's fastest-growing digital markets. Over 100 million users use ChatGPT weekly, demonstrating substantial demand for applications. In December last year, Microsoft announced plans to invest $17.5 billion in India over the next four years to expand cloud and AI infrastructure. Google's five-year, $15 billion investment plan includes establishing its first AI center in India. Amazon has committed $35 billion by 2030, focusing on promoting AI-driven digital transformation. The Indian government expects data center investments to reach $200 billion in the coming years. This influx of capital reflects global tech giants' recognition of India's market potential and its role as a testing ground for innovation.

However, India's shortcomings are equally evident. It has yet to develop a domestic large-scale AI foundational model capable of competing with the likes of OpenAI in the United States or DeepSeek in China. Analysts point out that there are three major bottlenecks behind this: limited access to advanced semiconductor chips, the nascent stage of high-performance data center construction, and the immense complexity of training AI models on India's over 100 major local languages. A professor of computer science at the Indian Institute of Technology Delhi remarked during a summit break: "We have top-tier engineers, but building large models requires sustained massive capital investment, top-notch hardware clusters, and long-term patience for fundamental research—this is precisely what we currently lack the most."

Geopolitical Chessboard: How India Leverages Its "Middle Path" Identity

The choice of venue and the list of participants for this summit itself convey geopolitical signals. As the first major global AI summit held in a Global South country, India deliberately played the role of a bridge. On one hand, Modi shared the stage with Macron, Pichai, and Altman, showcasing deep integration with the Western technology system. On the other hand, Secretary-General Guterres called for the establishment of a $3 billion global fund at the summit to help impoverished countries build basic AI capabilities, including skills training, data access, and affordable computing power, echoing the widespread demands of developing nations. India positioned itself as both the spokesperson for these demands and the provider of solutions.

This middle-path strategy stems from India's unique position. It is neither a full member of exclusive technological blocs such as the U.S.-led Chip 4 Alliance, nor is it entangled in the increasingly intense comprehensive technological decoupling between China and the United States. This enables India to draw resources from both sides: attracting massive investments and top-tier enterprises from the U.S., while maintaining connectivity with global supply chains, including some Chinese equipment. A European diplomat commented on-site at the summit: India is one of the few countries capable of engaging in candid dialogues simultaneously with Silicon Valley, Brussels, and the Global South. Such trust capital is highly valuable in the current AI governance negotiations.

Sam Altman's warning at the summit—that the concentration of this technology in one company or one country could lead to devastation—while pointing to a universal risk, was undoubtedly heard by the audience as an implicit reference to the unsustainable dominance of the current two powers, the U.S. and China. This provides India with a narrative space: a diverse, decentralized global AI ecosystem requires a third pole, and India, with its market scale, democratic system, and pool of engineers, is seen as a suitable candidate.

Practical Challenges: Bridging the Gap from Grand Vision to Concrete Implementation

Behind the glamorous scenes of the summit, episodes of organizational chaos exposed India's typical execution-level issues. On the opening day of the conference, attendees and exhibitors faced long queues and delays, while complaints about stolen personal belongings and exhibits surfaced on social media. On Wednesday, an Indian private university was expelled from the summit after its staff passed off a commercially manufactured Chinese robotic dog as the university's own innovation. An even greater embarrassment occurred on Thursday when Microsoft co-founder Bill Gates unexpectedly canceled his scheduled keynote speech. His foundation vaguely stated it was to ensure the focus remained on the key priorities of the AI summit. The outside world widely linked this to questions surrounding Gates' relationship with the late sex offender Epstein.

These organizational flaws, though at the meeting level, reflect deeper systemic challenges. An editorial in India's Financial Express points out: We excel at conceiving grand national missions, but we still stumble in coordinating public and private sectors, ensuring projects are delivered on time and within budget, protecting intellectual property, and establishing a seamless regulatory environment. India's ambitious National AI Strategy was proposed in 2018, yet key data governance bills and AI ethics frameworks remain under debate in parliament.

More pressing pressure comes from the socioeconomic level. 60% of India's workforce is engaged in low-productivity service industries, which are precisely the jobs most vulnerable to AI automation. Youth unemployment remains high, and the AI revolution may exacerbate this trend. In a sub-forum at the summit, the CEO of a tech startup from Bangalore stated bluntly: If we blindly introduce automation without large-scale skill reskilling of the workforce, AI will not bring a $4 trillion opportunity but rather a trigger for social unrest. Whether India can transform its demographic dividend into an AI dividend depends on the speed of its education and vocational training system reforms, which is far more challenging than hosting an international summit.

Global Governance: Can New Delhi's Voice Change the Game?

The summit concluded with the release of a joint statement signed by dozens of national leaders, committing to establishing a common language on AI risks and promoting the use of AI for the global common good. However, much like the previous three AI safety summits held in France, South Korea, and the UK, this statement remains broad in scope and lacks binding legal provisions or concrete funding commitments. Nikki Iliadis, Director of Global AI Governance at the Future Society think tank, commented: Governance of powerful technologies often begins with a common language—which risks matter, which thresholds are unacceptable. This is a necessary first step, but it is still far from a genuine global regulatory framework.

India's core demand is to ensure that global AI governance rules do not become tools for technologically advanced nations to consolidate their advantages. The Modi administration is actively pushing to include digital public infrastructure and affordable AI computing capabilities into the core agenda of global discussions—both are widely concerning for developing countries but receive less priority from the US and Europe. By hosting this summit, India has successfully placed these issues on the main table.

However, there is still a long way to go from having a voice to gaining rule-making power. Currently, the commanding heights of AI technology standards, chip manufacturing, and foundational model development remain firmly in the hands of the United States and China. Whether India can realize its vision of "Design in India" depends on whether it can develop irreplaceable competitiveness in application-layer innovation and solutions tailored to developing markets. An analysis report by the Indian think tank Observer Research Foundation suggests that India's best path may not be to directly replicate OpenAI's approach but to focus on vertical AI applications: for example, using AI to enhance agricultural yields, optimize diagnostic efficiency in its vast public healthcare system, or develop natural language interaction tools capable of handling multiple Indian dialects. In these areas, localized data and contextual understanding are more critical than sheer model scale.

As the summit concluded, a cautious optimism hung over New Delhi. India had declared its AI ambitions to the world and successfully positioned itself as an indispensable player in the global dialogue. However, the path to leadership is strewn with challenges: investment gaps, technological dependencies, geopolitical balancing, and domestic reforms. The global AI landscape is undergoing a dramatic transformation, and this time, India does not want to be merely a bystander or service provider; it aims to be a key player. Yet this game is extremely complex, with no room for regret in each move and time pressing. Over the next two years, whether the anticipated $200 billion in investments materializes and whether the first globally influential, homegrown Indian AI foundational model emerges will serve as the toughest benchmarks to test all the declarations made today.