India's AI Crossroads: Challenges and Opportunities in the Global AI Race

View: DeepSeek is India's final call to board the AI flight

India risks missing the AI revolution due to its risk-averse private sector, leaving it reliant on foreign technology. Despite deep indigenous talent, the country needs more significant government support and investment in foundational AI research to compete globally.The AI flight is taking off, and DeepSeek is the final call for India to show up at the boarding gate. Since its private sector is too risk averse to back research projects with uncertain payoffs, the state will have to step up. The Chinese startup's artificial intelligence models, which it began offering last month as open-source licenses, have been built at a fraction of the cost of resource-intensive rivals like OpenAI's ChatGPT or Google's Gemini. The US tech industry and Wall Street investors are rightly viewing DeepSeek as a disruptor. Silicon Valley firms are putting down hundreds of billion dollars to fend off the challenge. New York state has banned DeepSeek's AI assistant from government devices. India is watching the economic and political contest from the sidelines. That's dangerously complacent. Unlike in manufacturing or transportation, where it has already ceded a large lead to its neighbor, here's a race that's still wide open. But unless the most-populous nation puts its globally acknowledged edge in software programming to work, the moment will pass it by. DeepSeek is threatening the one comparative advantage the country has assiduously worked toward in the 21st century: code-writing on an industrial scale. "Let the code write itself," says DeepSeek Coder. The AI-based programming assistant, which has already made a splash in the development community, is bound to become more capable in the weeks and months ahead. Using such tools, a small, highly skilled section of India's 5 million code-writers will become tremendously more productive. For the majority, though, this will be bad news. Homegrown models, if they're cheaper to license than foreign AI, will get deployed faster. A surge in efficiency across industries will absorb the workers displaced from code-writing jobs. Putting shiny new tools in the hands of the 2.5 million-plus graduates and Ph.Ds minted annually in science, technology, engineering and medicine could lead to breakthroughs that end up lifting the economy. This is the link that policymakers are refusing to see. The $1.2 billion that New Delhi committed last year to the India AI Mission is a fraction of a $24 billion subsidy program for manufacturers. It's been nearly two years since Sam Altman was asked at a conference if an Indian startup could build a foundational model, trained on vast datasets and capable of multiple applications, for $10 million. The founder of OpenAI said that such an undertaking would be "completely hopeless." It's only natural for Altman to say that -- nobody wants their second-largest market by number of users to become a competitor. But what explains the lack of confidence on the Indian side? Even with DeepSeek calling Silicon Valley's bluff on costs, Indian tech companies are reluctant to take up foundational work in generative AI because success is not guaranteed. There is some investment going into adapting existing models to handle local languages, but foreign alternatives that will offer the same Indian-language capabilities plus a whole lot more will likely overshadow these efforts, according to Nilesh Jasani of GenInnov, a Singapore-based global innovation fund. China has ramped up its share of top-tier global AI talent to 47%, compared with 18% for America. India's figure is just 5% because most of its talent ends up migrating, largely to the US. Multinationals like GE Aerospace are doing sophisticated applied research in India using local engineering talent. But there simply isn't a supporting environment for deep fundamental research, and no urgency to build one. This is the situation eight years after a team of Google researchers gave shape to the language-processing architecture behind today's models. "Attention Is All You Need," was the title of their paper. Clearly, local tech policymakers weren't very attentive to the technology's potential, even though two of the eight scientists involved in that pathbreaking project are Indian-born. If the public sector has been lacking in attention, the private sector has been short on intent. Mukesh Ambani, the country's richest tycoon, recently announced that he would build the world's largest data center. He's buying Nvidia Corp. chips, which will be crucial for training models. Infrastructure alone won't be enough. Breakthroughs in natural language processing will come from hundreds of attempts at model-building, each costing a few million dollars. The software outsourcing companies of Bengaluru, India's Silicon Valley, should have been at the forefront of this initiative because of the threat GenAI poses to their bread-and-butter activity of code-writing for global corporations. Yet they aren't keen on taking bold bets. Their current business is still rewarding large shareholders with fat dividend checks and share buybacks, with little new investment. There's limited appetite for moonshots. The idea that India is the next China -- running just about a decade behind it -- was popular around 20 years ago. Back then, people wrote books about "Chindia." The South Korean financial industry even launched funds covering the two most-populous nations as a single theme. Two decades later, there isn't a lot left of that illusion of comparability. While India did attend to its basic infrastructure shortages like electricity and roads, China raised the gap between the two economies by lifting its technology game. Its arc of global dominance, which just 10 years ago was limited to a few industries like drones and solar panels, has extended to electric vehicles, high-speed trains, and now, generative AI. So when Indian tech companies say that they will profit from growing AI adoption by making customized digital assistants for global corporations, they're ignoring the inevitable progress of GenAI to AGI, or artificial general intelligence. Models that rival human cognitive abilities will handle most programming tasks on their own. Either OpenAI, or DeepSeek, will get there. Or, another model will succeed. For the South Asian country to not become a permanent importer of AI tools, it needs to own foundational technologies, built with massive government support for research universities and institutions. Above all, tech policymakers have to shake off their defeatist fatalism and heed the challenge facing them. Attention is everything.

India AI: As DeepSeek and ChatGPT surge, is Delhi falling behind?

A flurry of global AI leaders have also been talking up India's capabilities recently. After being initially dismissive, OpenAI CEO Sam Altman this month said India should be playing a leading role in the AI revolution. The country is now OpenAI's second largest market by users. Others like Microsoft have put serious money on the table - committing $3bn (£2.4bn) for cloud and AI infrastructure. Nvidia's Jensen Huang also spoke of India's "unmatched" technical talent as a key to unlocking its future potential. With 200 startups working on generative AI, there's enough entrepreneurial activity under way too. But despite having key ingredients for success in place, India risks lagging behind without basic structural fixes to education, research and state policy, experts say. China and the US already have a "four to five year head-start", having invested heavily in research and academia and developed AI for military applications, law enforcement and now large language models, technology analyst Prasanto Roy told the BBC. Though in the top five globally on Stanford's AI Vibrancy Index - which ranks countries on metrics such as patents, funding, policy and research - India is still far behind the two superpowers in many key areas. China and the US were granted 60% and 20% of the world's total AI patents between 2010 and 2022 respectively. India got less than half a percent. India's AI startups also received a fraction of the private investment that US and Chinese companies got in 2023. India's state-funded AI mission, meanwhile, is worth a trifling $1bn compared with the staggering $500bn the US has earmarked for Stargate - a plan to build massive AI infrastructure in the US - or China's reported $137bn initiative to become an AI hub by 2030.

DeepSeek Is India's Final Call to Board the AI Flight

The AI flight is taking off, and DeepSeek is the final call for India to show up at the boarding gate. Since its private sector is too risk averse to back research projects with uncertain payoffs, the state will have to step up. The Chinese startup's artificial intelligence models, which it began offering last month as open-source licenses, have been built at a fraction of the cost of resource-intensive rivals like OpenAI's ChatGPT or Google's Gemini. The US tech industry and Wall Street investors are rightly viewing DeepSeek as a disruptor. Silicon Valley firms are putting down hundreds of billion dollars to fend off the challenge. New York state has banned DeepSeek's AI assistant from government devices.

India's AI Revolution: Building Indigenous Intelligence for a Digital Future

China's DeepSeek AI recently accelerated the global AI race by launching a ChatGPT-like algorithm at a fraction of the cost, transforming the competition within the tech behemoths. Artificial Intelligence (AI) innovations are not about creating economic dominance; they are focused on securing technological independence. Therefore, India cannot afford to be a mere spectator in this high-stakes game. India ranks third in AI research after China and the US and fourth in the Global AI Vibrancy Rankings. According to Niti Aayog, AI is expected to boost the annual growth rate by 1.3% by 2035, adding $1 trillion to the economy. The country's AI market is driven by the vast pool of skilled workforce and professionals in STEM fields. They are relentlessly working to create AI algorithms, applications, and solutions across industries to fulfil the evolving demands of the domestic and global markets.