The report also noted that India’s stock market has lower concentration compared with major global markets, offering greater diversification.
India has emerged as one of the top countries in artificial intelligence (AI) readiness, trailing only the U.S. and China, while remaining one of the world’s least concentrated equity markets, according to a recent report by J.P. Morgan.
The report, titled “Semiquincententacles: The U.S. Grip on Global Markets at 250,” highlighted India’s unique position in global capital markets and the evolving AI and semiconductor landscape.
India among least concentrated equity markets globally
Comparing stock market concentration across countries, the report noted that while the share of the ten largest companies in the S&P 500 has risen sharply in recent years, India remains among the least concentrated markets globally.
“As recently as 2015, the 10 largest U.S. stocks represented just 17% of the S&P 500’s market capitalization… Now this figure has risen to ~40%,” the report said.
However, it added that “40% concentration still ranks among the three lowest equity concentration figures in the world; only Japan and India have less.”
US leads AI race, China narrows gap
The report also underscored the growing dominance of the United States in artificial intelligence and advanced computing, particularly in semiconductors and AI infrastructure.
According to the report, “the U.S. is the most vibrant and prepared country for AI, with China close behind on some measures.”
In Stanford University’s Global AI Vibrancy Index, cited by the report, the United States ranked first, China second, and India third. The index measures countries across parameters including research and development, infrastructure, education, policy, governance, and economic readiness.
India’s AI readiness improves but gaps remain
The report further observed that the United States continues to maintain a commanding position in AI-related productivity gains and technological innovation.
“Whether the issue is labor productivity or total factor productivity, the U.S. leads the G10,” it said, adding that productivity growth in the information and data-processing sectors accelerated significantly following the launch of generative AI tools.
Semiconductor race and China’s growing influence
On semiconductors and AI hardware, the report highlighted the central role of U.S. companies in the global accelerator market. It noted that Nvidia continues to dominate AI accelerator revenues, although competition from custom chips developed by hyperscalers such as Google, Amazon, Microsoft, and Meta is increasing.
At the same time, the report pointed to the rapid advancement of Chinese AI models and growing competition from China within the AI ecosystem.
Referring to cost-efficient AI models, the report said that the “efficient frontier” in intelligence-per-dollar is “dominated by China (DeepSeek, MiniMax, Xiaomi, Alibaba),” with only a limited presence from U.S. models.
It further noted that “Chinese models appear as triangles, U.S. models as circles” in comparative assessments of AI model performance and operating costs.
China gains ground with cost-efficient AI models
The report cited the growing adoption of Chinese AI models by businesses seeking lower costs. It noted that “OpenRouter shows a surge in API calls to Chinese models” and that, by April 2026, leading Chinese open-weight models “scored within a few dozen Elo points of closed frontier models and cost 10x-50x less per token.”
Despite China’s progress, J.P. Morgan maintained that the United States remains the global leader in AI innovation, infrastructure, and investment, while warning that policy restrictions and supply-chain vulnerabilities could affect its future lead.
For India, the report’s findings suggest a strengthening position in AI readiness and global market diversification. However, the country remains far behind both the U.S. and China in overall AI capabilities and semiconductor ecosystem development.
Published on June 24, 2026
