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India Can Become AI Skill Capital: IBM India MD

CIO Insider Team | Thursday, 14 May, 2026
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India could position itself as the world’s leading AI talent hub by significantly expanding its AI-skilled workforce by 2030, according to Sandip Patel, Managing Director of IBM India and South Asia.

Speaking on the sidelines of the launch of the joint IBM-IndiaAI report, “From Promise to Power: How AI is Redefining India’s Economic Future,” Patel said India already possesses one of the world’s largest AI-aware workforce bases.

He noted that accelerating AI literacy and upskilling across industries could help the country establish itself as a dominant force in the global AI talent ecosystem.

Patel highlighted that India currently has an addressable workforce of nearly 600 million people, of which close to 30percent — approximately 200 million workers — are already AI literate. He described this as an extraordinary foundation for future growth and innovation.

Also Read: Delhi Seeks AI Collaboration with Startups, Tech Companies

“That is a massive number,” Patel said, adding that if AI literacy levels expand to nearly 60percent by 2030, India could emerge as one of the most influential contributors to the global AI economy.

According to Patel, the rapid global demand for AI-skilled professionals presents India with a unique opportunity to become the world’s AI skill capital, supplying talent, innovation, and digital expertise to enterprises and governments worldwide.

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Patel cautioned that many organizations are still struggling to move AI initiatives beyond pilot stages due to operational and structural bottlenecks

The IBM-IndiaAI report estimates that artificial intelligence could contribute more than $500 billion to India’s economy by 2030, as enterprises increasingly view AI as a critical driver of productivity, competitiveness, and long-term economic growth.

However, Patel cautioned that many organizations are still struggling to move AI initiatives beyond pilot stages due to operational and structural bottlenecks.

Also Read: Meta Turns To Space To Power AI Systems Of The Future

He identified data readiness as one of the biggest challenges, while also emphasizing the need for stronger AI governance, trust frameworks, and responsible AI practices to ensure reliable and scalable outcomes across industries.



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