India’s Strategic Approach to AI Utilization
The global race in artificial intelligence is often evaluated by assessing who possesses the largest models, the most advanced chips, and vast data centers. However, Shri Ashishkumar Chauhan, CEO of the National Stock Exchange of India, believes these metrics may not define who benefits economically from AI advancements. According to Chauhan, being the best users of AI technology is more critical than being its inventors. He shared this perspective during Newsweek’s July 27 ‘AI Impact Forum’ webinar.
Chauhan emphasized that India might gain a significant advantage by integrating AI into businesses, services, and everyday devices, even if the core technology originated elsewhere. A warning from Bernstein, a global equity research firm, suggested that India might remain a ‘permanent customer’ of AI technologies from the US or China. Chauhan countered this by reflecting on India’s technological history, noting that while India did not invent computer chips, operating systems, or programming languages, it still built a global industry by mastering these technologies and solving complex problems for international companies.
‘The battle of LLMs [Large Language Models] is over,’ Chauhan remarked, expressing his belief that open-source models will prevail due to their potential to lower experimentation costs and adapt to various uses in phones, vehicles, and industrial equipment.
Chauhan anticipates a shift in economic value towards companies and countries that efficiently apply AI to practical, cost-effective solutions. With its large pool of technology service professionals, India is well-positioned for this competition. These professionals already empower global companies by building and supporting systems, gaining experience with evolving business processes due to AI integration.
The widespread use of smaller AI models could further democratize access to AI. Chauhan foresees that AI processing will increasingly occur on devices like phones, as computing becomes more affordable and systems more customizable. Large models will continue to serve complex needs, while smaller models handle everyday tasks. Nations adept at using both will potentially gain more value than those focused on building massive systems exclusively.
Chauhan challenges the traditional measures of innovation. Despite India’s relatively low R&D spending, he argues that Indian engineers often conduct significant research for international firms, even if recognition goes elsewhere. Many eventually leave to establish their own businesses, driven by commercial opportunities rather than centralized plans. This system requires innovations to be both cost-effective and high-quality.
Infrastructure development, particularly in semiconductor manufacturing and renewable energy, is crucial for AI deployment. With data centers increasing energy demands, India is exploring sustainable energy sources, including nuclear power. Chauhan cautions against assuming permanent shortages or valuations, highlighting that overinvestment in data centers and semiconductor production might lead to excess capacity if AI revenues do not meet expectations.
‘It’s going to be a garden with many flowers of different types and not one single type of flowers,’ Chauhan expressed, predicting a more diverse future for AI development driven by open-source flexibility.
This diversity aligns with India’s strengths, suggesting that the nation does not need to lead in AI model development to prosper technologically. Energy, cost advantages, and technical expertise are likely pathways to success in technology workforce expansion and global market product development.
Chauhan advises AI entrepreneurs to prioritize financial prudence, keeping expenses below income to allow more room for development and innovation. He illustrated this with a simple financial principle: ‘Who is the richest person on the earth? The person who spends less than his income.’