India‘s AI Race: Can it Catch Up to china and the US?
Two years after ChatGPT’s global debut, China‘s DeepSeek has dramatically reduced the cost of generative AI request growth, igniting a renewed global AI race. India, however, lags, especially in developing foundational language models—the core of chatbots and similar applications. This technological gap presents a significant challenge for a nation aiming for global AI leadership.
The Indian government aims to bridge this gap. It pledges to provide startups, universities, and researchers with thousands of advanced chips within 10 months to accelerate growth. This ambitious plan follows endorsements from global AI leaders like OpenAI CEO Sam Altman, who declared that India should be playing a leading role in the AI revolution
. OpenAI’s significant user base in india, second only to its home market, underscores the country’s potential. Microsoft’s ample $3 billion investment in Indian cloud and AI infrastructure further bolsters this optimism.
With 200 startups already engaged in generative AI, entrepreneurial activity is robust. Though, experts caution against complacency. Technology analyst Prasanto Roy warned on the BBC that China and the US possess a “four to five year head-start,”
due to substantial investments in research,academia,and military and law enforcement AI applications,including large language models. This head start translates to a significant advantage in the global AI landscape.
While India ranks among the top five globally on Stanford’s AI Vibrancy Index, considering factors like patents, funding, policy, and research, it significantly trails the US and China in crucial areas. Between 2010 and 2022, China and the US secured 60% and 20% of global AI patents, respectively, while India’s share was less than half a percent. Similarly, Indian AI startups received a minuscule portion of the private investment flowing to US and Chinese companies in 2023. India’s state-funded AI mission, valued at $1 billion, pales in comparison to the US’s $500 billion Stargate initiative and China’s reported $137 billion plan to become a leading AI hub by 2030.
jaspreet Bindra, founder of an AI literacy consultancy, highlights a lack of “patient” long-term capital as a major obstacle.Bindra notes that while DeepSeek’s development reportedly cost $5.6 million, “there was much more capital behind it.”
The scarcity of high-quality, India-specific datasets for training AI models in regional languages like Hindi, Marathi, or Tamil further complicates matters, given the country’s linguistic diversity. This data scarcity hinders the development of truly inclusive and representative AI systems.
Despite these challenges, India possesses a significant advantage: 15% of the world’s AI workforce hails from the country. Though, Stanford’s research reveals a concerning trend: increasing numbers of Indian AI professionals are emigrating. Bindra attributes this partly to the fact that “foundational AI innovations typically come from deep R&D in universities and corporate research labs,”
areas where India currently lacks a robust supporting surroundings. This brain drain poses a serious threat to India’s long-term AI goals.
Bindra advocates for replicating the success of India’s payments revolution, achieved through strong government-industry-academia collaboration. The Unified Payments Interface (UPI),a government-developed digital payment system,has transformed digital transactions in India.Bengaluru’s massive $200 billion outsourcing industry, home to millions of coders, has yet to fully embrace foundational consumer AI technologies, leaving a significant gap for startups to fill, according to Roy.
Roy expresses skepticism about the government’s ambitious 10-month timeline for developing a DeepSeek competitor, calling it a “knee-jerk reaction.”
He predicts that “I don’t think India will be able to produce anything like DeepSeek at least for the next few years.”
Bhavish Agarwal, founder of Krutrim, an early Indian AI startup, suggests leveraging existing open-source platforms like DeepSeek to accelerate progress. Though, experts emphasize the long-term necessity of developing a foundational model to ensure strategic autonomy, reduce import dependencies, and mitigate the risk of sanctions.
India’s AI journey requires significant advancements in computational power and hardware infrastructure, including semiconductor manufacturing, before it can meaningfully close the gap with the US and china. This requires a multi-pronged approach encompassing investment, education, and strategic partnerships.
Headline: navigating India’s AI Ambitions: Bridging the Technological Divides Amidst Global Giants
Opening Remark:
the world is deeply engaged in an AI race, with giants like the US and China leading the charge. But what about a nation with a tech-savvy workforce yearning for a seat at this groundbreaking table? Can India catch up, or is it in a perpetual game of catch-up? Let’s delve into this south Asian contender’s journey towards AI excellence.
Editor: Let’s begin by addressing the elephant in the room: India finds itself trailing both the US and China in the AI race. What makes the Indian AI landscape unique despite these challenges?
Expert: India’s AI landscape is indeed rich and multifaceted, characterized by an immense human resource potential—about 15% of the world’s AI workforce is Indian. This is a monumental advantage.However, unlike its global peers, India’s efforts are largely dispersed across various startups rather than concentrated in large-scale projects. The key challenge lies in inadequate foundational investments, notably in semiconductors and large language models, those essential building blocks of advanced AI capabilities. Historical underinvestment in academic R&D further accentuates this divide.
Editor: You mentioned the critically important investment by countries like the US and China,with India’s allocation appearing modest in comparison. how critical is governmental financial support for India’s progress in AI, and what lessons can be learned from other nations?
Expert: Financial investment is indeed pivotal. Comparatively, the US’s $500 billion Stargate initiative and China’s massive $137 billion AI development plan are dauntingly enterprising. India, with its $1 billion AI mission, must rethink its strategy. A major takeaway from both the US and China is their robust synergy between government funding and private sector engagement, fostering innovation clusters and research hubs. India’s public sector alone might not suffice; thus, incentivizing private investment is crucial. The Unified Payments Interface (UPI) is a testament to the accomplished government-industry collaboration that can serve as a blueprint for AI initiatives.
Editor: Despite formidable overseas competition, India boasts a vibrant startup ecosystem engaged in generative AI. How might these startups overcome the current technological hurdles to develop Indian-specific AI solutions?
Expert: Startups are India’s cornerstone in the evolving AI sector. A promising strategy is to leverage open-source AI models, particularly those developed by leaders like DeepSeek.US and Chinese startups can serve as models—utilizing open-source to build upon with localized data and innovation. However, the paucity of high-quality, India-specific datasets, crucial for training AI models, poses a serious hurdle. Targeted efforts in data collection—especially in regional languages—are essential. Innovation in this arena could democratize AI,rendering it relevant and accessible across linguistic and cultural landscapes.
Editor: The brain drain of AI professionals is quite concerning for India’s future in AI. How can India retain its talent and ensure robust foundational research in AI?
Expert: Retaining talent requires creating an invigorating research environment that promises intellectual stimulation and resourceful facilities. Enhancing collaborations between academia and industry can offer avenues for practical applications of research, enticing professionals to stay. Historical parallels from the tech industry suggest that nurturing young innovators through incubators and providing platforms for their ideas can reduce the allure of emigration. government policies fostering clear career pathways in AI research, paired with competitive remuneration and infrastructure, will be crucial in stemming the brain drain.
Editor: What should be India’s immediate priorities to realistically meet its AI policy goals and eventually create its own foundational AI models?
Expert: The immediate steps should include:
- Investment in Infrastructure: Addressing the semiconductor deficit is crucial. Expanding domestic manufacturing capabilities will reduce dependency on imports.
- Data Development: Prioritize the creation of extensive datasets in regional languages, fostering AI literacy and engagement across diverse demographics.
- Research Funding: Escalate funding for academic and corporate research labs in foundational AI, akin to the synergistic model seen in the US and China.
- Government-Promoted Collaborations: Replicate the UPI’s model success through strategic collaborations between government, academia, and the private sector.
- Talent Retention Strategies: Establish initiatives that retain local talent through robust career opportunities and fostering innovation domestically.
These strategic efforts are not shortcuts but foundations for enduring progress toward becoming a global AI leader.
Closing Thought:
India stands at a crucial juncture—the path to pursuing an AI-driven golden age is challenging but not insurmountable. By capitalizing on its workforce and fostering strategic partnerships, India could indeed craft its own narrative in the global AI saga. Would you agree that this is the opportune time for India to redefine its technological destiny? Join the conversation below, and share your views on how India can emerge as a formidable force in the global AI landscape.