-
CENTRES
Progammes & Centres
Location
Image Source: Getty
The Artificial Intelligence (AI) landscape is evolving rapidly, and 2025 began with a seismic shift: the launch of DeepSeek, a Chinese AI model that disrupted the American-dominated AI space. Its emergence was particularly significant, as it was developed despite US trade and tech restrictions, proving that AI innovation is no longer confined to regions with unrestricted access to cutting-edge hardware. This breakthrough lowers barriers to entry, signalling that other nations may soon follow suit, building their own AI ecosystems independent of traditional tech powerhouses.
A useful way to analyse this shift is through the lens of technology creators versus technology users—distinctions that often mirror the economic realities of developed and emerging markets. Developed economies, with their deep research and design (R&D) investments and established innovation ecosystems, continue to lead AI breakthroughs. Meanwhile, developing markets, characterised by rapid industrialisation and expanding consumer bases, have immense growth potential but still rely on external capital and expertise for AI development.
Developed economies, with their deep research and design (R&D) investments and established innovation ecosystems, continue to lead AI breakthroughs.
This divergence raises critical questions: Will AI creation remain concentrated in wealthier economies, or will the democratisation of AI tools allow emerging markets to become serious players? The coming years will reveal whether we are witnessing the fragmentation of AI leadership or the dawn of a more multipolar AI ecosystem.
The question posed above is undoubtedly important, yet it remains somewhat reductive and necessitates a more nuanced approach. While the democratisation of AI and its expansion across multiple nations is often seen as an unequivocal positive, it inherently introduces a critical new dimension: competition.
The competitive dynamics of AI development can be analysed through multiple dimensions, with two particularly crucial aspects standing out. First, the strength of a country’s domestic market plays a significant role in shaping its AI trajectory. This includes not only the scale and maturity of its startup ecosystem but also the extent to which private enterprises are both developing AI solutions and integrating them into their business operations. A robust domestic market fosters innovation, attracts investment, and ensures that AI advancements actively contribute to economic productivity and industry transformation.
China’s AI strategy has been driven by substantial government-backed venture capital investments, with nearly $912 billion allocated over the past decade—of which approximately 23 percent (around $209 billion) has been directed toward AI firms. This underscores Beijing’s strategic intent to position itself as both a creator and a user of AI, leveraging state-backed funding to accelerate domestic innovation and industrial adoption.
A robust domestic market fosters innovation, attracts investment, and ensures that AI advancements actively contribute to economic productivity and industry transformation.
India, by contrast, has yet to establish itself as a major AI producer but is rapidly emerging as a leading adopter of AI technologies. According to an IBM report, nearly 59 percent of IT professionals in India indicate that their organisations have integrated AI into business operations, placing the country among the global leaders in AI deployment. However, at least for now, the contrast with China remains stark: while China is both developing and implementing AI at scale, India remains primarily a consumer rather than a creator of AI technologies. This difference in approach was recently highlighted by India’s Commerce Minister Piyush Goyal, who observed that while India is building food and hyper-delivery apps, China is investing aggressively in AI and electric vehicles. Rather than viewing this as a critique of India’s vibrant startup ecosystem, it may be more apt to see it as a reflection of the distinct developmental paths and national priorities of the two countries.
The second key dimension of competition lies in how governments are integrating AI into their capabilities, particularly in military operations and intelligence services. India and China are both integrating AI into their military strategies, but with differing focuses and levels of advancement. India is leveraging AI primarily for surveillance, reconnaissance, logistics, and cybersecurity, with notable developments such as AI-enabled drone swarms and the launch of seventy-five AI-based defence products. In contrast, China is making more aggressive strides in military AI, investing heavily in autonomous weapons, missile guidance systems, and AI-enhanced command structures. While India is steadily adopting AI in defence, China’s advancements in autonomous warfare and decision-making systems suggest a more rapid and expansive military AI deployment.
While China’s lead in AI growth and adoption is undeniable, this should not be seen as an indictment of India’s progress but rather as a testament to China’s remarkable advancements in the field. The scale and pace of China’s AI expansion reflect its strategic prioritisation of emerging technologies, backed by substantial investment and state support. This dominance extends beyond AI, spanning across multiple areas of tech innovation and reinforcing China’s global rise.
The scale and pace of China’s AI expansion reflect its strategic prioritisation of emerging technologies, backed by substantial investment and state support.
The Australian Strategic Policy Institute's (ASPI) Critical Technology Tracker reveals China's significant advancements across various critical and emerging technologies. According to the tracker, China leads in thirty-seven out of forty-four technologies monitored, spanning sectors such as defence, space, robotics, energy, biotechnology, AI, advanced materials, and quantum technology. This dominance is further highlighted by China’s research output: in certain technologies, all of the world's top ten leading research institutions are based in China, collectively producing nine times more high-impact research papers than the second-ranked country, often the US.
The emergence of DeepSeek has reignited discussions about global tech competition—whether in the context of US-China rivalry or the monopolistic tendencies of dominant AI models. For India, these advancements serve as valuable case studies—an indirect testing ground from which critical lessons can be drawn.
In recent years, the Indian government has sharpened its focus on AI development, through substantial funding commitments and policy initiatives. While DeepSeek demonstrated that the capital-intensive AI model dominated by the United States is not impervious to disruption, investment remains a fundamental driver of progress in this domain. For India to develop its own equivalent of ChatGPT or DeepSeek, a robust financial and institutional framework will be critical. However, India possesses a unique advantage: an expansive pool of young, highly skilled engineers who could form the foundation of AI innovation. This potential is further amplified by rising internet penetration and improving digital literacy, both of which could accelerate AI adoption and, in turn, create positive spillover effects for domestic AI development.
The intersection of a rapidly growing digital economy, a skilled workforce, and expanding technological infrastructure positions India as a potential leader in AI innovation and deployment.
Furthermore, India’s vast market size presents a compelling case for the development of an indigenous AI ecosystem. As AI adoption becomes increasingly widespread across various sectors within the country, the demand for domestically developed AI tools is both a strategic necessity and an economic opportunity. The intersection of a rapidly growing digital economy, a skilled workforce, and expanding technological infrastructure positions India as a potential leader in AI innovation and deployment.
For a country like India, the development of AI must be approached through multiple strategic lenses. While investment and talent cultivation remain crucial, a broader geopolitical and trade perspective is equally imperative. In an increasingly multipolar world, India has the potential to emerge as a leading tech power, particularly within the Global South—an ambition it has previously demonstrated through initiatives such as its G20 presidency in 2023. To translate this vision into tangible outcomes, India must prioritise the development of an indigenous AI model capable of competing with leading global counterparts. This would enable it to transition from being merely an adopter of foreign technologies to a producer and provider of cutting-edge AI solutions. Given its vast talent pool, growing digital infrastructure, and expanding AI ecosystem, India possesses the requisite resources to achieve this objective.
This commentary originally appeared in Lee Kuan Yew School of Public Policy.
The views expressed above belong to the author(s). ORF research and analyses now available on Telegram! Click here to access our curated content — blogs, longforms and interviews.
Dr Sameer Patil is Director, Centre for Security, Strategy and Technology at the Observer Research Foundation. His work focuses on the intersection of technology and national ...
Read More +
Sauradeep is an Associate Fellow at the Centre for Security, Strategy, and Technology at the Observer Research Foundation. His experience spans the startup ecosystem, impact ...
Read More +
PREV
