India’s deep and scalable AI talent pool makes it an attractive hub for such functions, Lalit Ahuja, CEO of consultancy ANSR, told FT. He noted that GCCs are becoming the “strategic AI backbone” of many organisations.
Supermarket chain Tesco, for example, repurposed its GCC in 2019 to focus on AI-based solutions that cut operational costs. Sumit Mitra, CEO of Tesco Business Solutions, told FT that the Bengaluru-based centre, with nearly 5,000 employees, shifted from “labour arbitrage” to “intellectual arbitrage”. One of its major contributions—centralised refrigerator temperature monitoring—has saved millions of pounds annually in food waste.
Despite having one of the world’s largest pools of tech workers, India lags behind the US and China in AI innovation. GCCs could help bridge that gap by offering access to advanced resources such as large language models from global firms.
These centres allow companies to keep AI development in-house, turning them into innovation hubs that can feed new technologies back into global operations, said Rohan Lobo, south Asia lead for GCCs at Deloitte.
GCCs have moved ahead from routine support roles to high-value tasks such as agentic AI and advanced analytics, said Jaspreet Singh, head of Grant Thornton Bharat’s GCC practice. However, challenges persist in limited digital and physical infrastructure outside major cities, and there is an urgent need to train and retain talent, he added.
India’s back office industry has grown from $11.5 billion in 2010 to $65 billion in 2023, employing 1.8 million people. Brokerage Goldman Sachs reports that research and development now makes up 55% of GCC revenue.
Cost edge of Indian AI talent
India also has an advantage in price amid the current AI talent war, which may lead to some jobs in the space being routed here.
Indian AI talent generally costs around 15–25% of what companies pay in global hubs such as the US, particularly for senior and research-level roles, according to AMS data.
Salaries in the US, UK or Europe are almost five times more than the Indian average for similar skill sets, as per Teamlease Digital. For mid-level skill roles, such as machine language engineers or data scientists with experience, the salary difference is about two to three times.
