Global Capability Centres (GCCs) in India are increasingly becoming critical environments where early-stage AI concepts are tested, refined, and scaled into global products.
At a Chennai-based GCC of TransUnion, over 80 ideas were pitched by a 300-member team during a hackathon. While many did not progress, a few moved into global product pipelines, built by the same teams. Today, 58% of Indian GCCs are investing in agentic AI and 83% in generative AI, turning India into a high-impact testing ground due to its diverse data and user base. Nearly 70–80% of TransUnion’s core technology development is now driven from India.
“Many of the AI systems which are built today sit on legacy operating models. For AI to be successful, domain expertise and technology should come together. Building cross-functional teams is critical so that domain-led innovation can actually happen,” said Debasis Panda.
GCCs are now widely used to test AI systems across banking, retail, and healthcare. Use cases include fraud detection, supply chain forecasting, pricing models, and customer service automation. About 67% of centres have dedicated AI teams, making these hubs cost-effective and low-risk experimentation zones.
India’s role is evolving beyond testing. At The Standard India, teams are building “greenfield capabilities” across AI, data platforms, and digital transformation. “Today, with the depth of engineering talent, strong data capabilities and growing domain expertise within GCCs, India is contributing not just to testing AI-led solutions but to shaping how those solutions are designed and deployed globally,” said Mohua Sengupta.
Decision-making is also shifting to India. “In many global organisations today, core technology frameworks… are being designed and validated in India before being rolled out globally,” said Ram Chandnani.
However, rapid innovation comes with risks. “If our AI has bias or hallucination, it’s a huge risk to the ecosystem,” said Ganesh Baliga, highlighting the need for strong governance. Companies are now embedding checks from development to deployment.
India’s high-variance data environment helps stress-test AI models, but it also adds complexity. “A model that works (or fails) in India does not necessarily generalise to US prime lending or European insurance risk pools,” said Aditya Gandhi.
From software to aerospace, GCCs are expanding their role. Thales’ India teams are already working on safety-critical aviation systems, reflecting how these centres are moving from testing zones to global innovation engines.
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