The global race for AI supremacy often focuses on entities with the largest models, most advanced chips, and biggest data centers. However, Shri Ashishkumar Chauhan, CEO of the National Stock Exchange of India, presents a different perspective. He suggests that economic gains may not necessarily be determined by these metrics alone. ‘You don’t have to be inventing something to be the best users,’ Chauhan emphasized during Newsweek’s ‘AI Impact Forum’ webinar, questioning India’s position on the AI trade.

Chauhan argues that India has the potential to gain an upper hand by integrating AI across business operations, services, and everyday devices, even if most of this technology originates from elsewhere. He reflects on India’s historical approach to technology—like the adoption of computer chips and operating systems where India wasn’t the creator but excelled as a user.

In response to a warning from Bernstein, a research and brokerage firm, about India becoming a ‘permanent customer’ to AI models developed in the US or China, Chauhan notes India’s history of not inventing but optimizing technologies to build a global industry. This background forms a foundation for Indian businesses to adapt AI for practical applications effectively.

Chauhan sees a new opportunity with AI. Open access to models can reduce experimental costs. Smaller AI systems can be tailored for devices like phones and vehicles without needing expansive infrastructure. He recalls predicting in 2025 that open-source systems would prevail over others.

While developers and infrastructure providers currently capture much attention, Chauhan foresees a shift. Economic value will increasingly accrue to entities capable of implementing AI affordably. With millions of tech service employees, India has experience in business processes ripe for transformation through AI.

Chauhan anticipates AI processing making its way into more everyday devices as costs drop and systems become customizable. Open technology permits local adaptation without continual reliance on centralized platforms. Large, highly advanced models will handle sophisticated tasks, while smaller, smart models will manage routine operations.

Chauhan challenges existing innovation metrics, noting India’s lower research expenditure. He explains that Indian engineers often perform research for foreign firms, reflecting activity not visible in official spending figures. Many later become entrepreneurs, founding new companies. He describes India’s entrepreneurial landscape as responsive to emerging market opportunities rather than relying on national innovation plans.

Infrastructure plays a significant role in AI deployment. India is increasing semiconductor manufacturing, expanding renewable energy, and exploring nuclear technologies to meet rising electricity needs for computing facilities. Chauhan advises patience, suggesting that the reported shortages and valuations may not persist if AI-generated revenues fail to meet expectations.

Regarding closed-model AI companies, Chauhan expresses skepticism about concentrated control over AI’s value. He envisions a diverse ecosystem of models, suggesting open-source competition will prompt cost-effective innovation and developer freedom.

India’s strength lies not in leading all aspects of AI development but in leveraging existing skills and resources. Chauhan advises AI entrepreneurs to remain fiscally prudent, keeping costs under revenue to allow for long-term growth and experimentation. This approach aligns with India’s future in AI deployment, harnessing its unique advantages to foster technology growth.