India’s Global Capability Centres (GCCs) have moved far beyond their origins as cost-efficient back offices. They are now strategic engines shaping products, driving research, and defining the technology stacks for global enterprises. This evolution was in sharp focus in the opening episode of Season 2 of Forbes India presents The Data Circle – India’s Changemakers, in association with Snowflake.
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Under the theme ‘GCCs for Global Growth – Building India’s Gen AI Powered Tech Stack for the World’, leaders from diverse industries, like Jayesh Prajapati, Head – Pune Technology Centre, SLB, Monica Chourasia, Executive Director and India Head of Technology, Kaiser Permanente, Pankaj Vyas, CEO and MD, Siemens Technology & Services, and Sujit Cheruvatath, Managing Director and Head of GCC Markets, Snowflake, outlined how India can lead in the age of generative AI. The conversation moved seamlessly between sectors, revealing a common playbook where trusted data, domain expertise, and adaptive talent converge to deliver global impact.
From Oilfields to Operating Theatres
Across industries, the panellists showed that Gen AI’s potential is no longer theoretical. At SLB’s Pune Technology Center, Jayesh Prajapati described how a global data-and-AI platform is enabling ‘conversational insight’, allowing specialists to query vast stores of unstructured data naturally. With “90 per cent of unstructured data not even mined yet,”, as per Jayesh Prajapati, the stakes are high in an energy sector with big operational and safety concerns.
The need for precision is even greater in healthcare. Although AI is now proficient at identifying tumours and predicting disease progression, Monica Chourasia stressed that algorithms must be embedded in clinical reality. After all, an AI model for healthcare is not simply a software but a decision-maker where the margin for error is zero.
Mastering data is possible through integrated data structures, as Pankaj Vyas demonstrated with the example of Siemens’ smart factories, where daily data flows equivalent to 4000 HD movies have been leveraged with ‘industrial co-pilots’ and digital twins, that convert this torrent into a continuous feedback loop, accelerating training, improving safety and optimizing emissions.
The Architecture of Adoption
Despite sectoral differences, successful AI deployment rests on common pillars. Jayesh Prajapati framed them as trust, agility, and scalability. Monica Chourasia added co-creation to the mix, bringing technologists, domain experts, and end-users together, to build solutions grounded in reality.
Sujith Cheruvatath tied these principles back to data infrastructure. “We want to bring AI to your data rather than take your data to AI,” he said, describing how Snowflake unifies structured, semi-structured, and unstructured data across clouds, enabling models from Anthropic, OpenAI, Llama, and others. Solid data security and governance allows collaboration without compromising compliance.
The Human Imperative
If Gen AI is the engine, people are both drivers and engineers. All four leaders agreed that AI literacy must be paired with deep domain mastery. At SLB, every employee undergoes function-specific AI training, so engineers and data scientists speak the same technical language. At Kaiser Permanente, even technically adept hires are immersed in US healthcare systems before writing code.
Retention, Monica Chourasia observed, demands more than competitive pay. Career mobility, continuous learning, and genuine ownership of outcomes are critical. Snowflake’s ‘1 Million Minds’ programme offers open and customer-specific training labs, hackathons, and workshops in an attempt to bridge the persistent academia-industry gap in India.
Looking Ahead
In the future, the panelists saw GCCs operating at the very top of the global value chain. Jayesh Prajapati pointed to agentic frameworks as a likely inflection point. Monica Chourasia envisioned a hyper-personalised, predictive healthcare platform that scales globally while enhancing patient outcomes. Sujith Cheruvatath urged India’s 1,800-plus GCCs to establish dedicated data-and-AI centres of excellence, while Pankaj Vyas spoke of an era of ‘democratised intelligence’, where people, machines, and digital systems share real-time, decision-grade insight.
A Defining Moment
The message from the first episode was clear. GCCs cannot afford to wait for permission to define their role in the Gen AI revolution. Those that act now will not simply execute global strategies, but shape them. In doing so, India’s GCCs can position themselves as strategic brain trusts, influencing how enterprises think, work, and innovate in an age defined by generative intelligence.
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