India’s GCCs to Become AI Transformation Engines by 2030: Dell-Zinnov

Dell Technologies, in partnership with Zinnov, released a report at Dell Technologies Forum 2026 titled “India GCCs 2030: From Capability Centers to Agentic Transformation Engines,” drawing on surveys and interviews with more than 50 senior GCC leaders across BFSI, retail, manufacturing and software sectors. The report concludes that the GCCs poised to lead by 2030 will not be those running the most AI pilots, but those that have built the foundations to scale AI into measurable enterprise outcomes.

India hosts over 2,100 GCCs employing 2.36 million people and generating $98.4 billion in revenue in FY26. About 64% of GCC leaders hold dual global mandates, running the India centre while owning a global function, and 70% have a defined AI roadmap. Indian GCCs account for approximately 28% of global GCC AI talent, with over 1,200 centres having built AI and machine learning capabilities. Around 66% of GCC leaders already rank top-line business impact as a high priority for their enterprise AI strategy.

The maturity curve is compressing: 27% of new GCCs now reach “Portfolio Hub” maturity within five years, compared to nearly a decade historically, with AI mandates arriving earlier in the journey. However, nearly 70% of GCCs remain stuck at the pilot stage, unable to consistently move proofs of concept into sustained enterprise adoption, constrained by fragmented data, legacy systems, unclear governance and talent models built for a pre-AI world.

According to the report, AI pilots stall for structural reasons, including messier production data, governance addressed after deployment rather than built in, and use cases that are difficult to integrate at scale. Agentic workflows can consume between 10,000 and 500,000 tokens per workflow, compared to 1,000-2,000 for a standard chat interaction, making early infrastructure decisions critical for cost and control. With 55% of routine GCC work already exposed to AI-driven automation and 60% of the workforce requiring reskilling by 2030, the report calls for workforce redesign to shift talent from repetitive execution toward engineering, product and business problem-solving.

The report identifies four levers for the next phase of GCC evolution: building repeatable AI-enabled workflows, planning AI architecture as an integrated decision covering data, compute, security and governance, taking genuine ownership of products and business outcomes, and redesigning workforce roles. It also introduces a framework for deciding which AI workloads to own versus consume through leased environments, along with a “Sovereign Sandbox” model for GCCs to experiment with regulated or proprietary data before moving workloads to production.

“The most influential GCCs of 2030 will not be measured by the number of AI initiatives they launch, but by their ability to industrialize AI responsibly and at scale. As they take on greater strategic ownership, robust foundations across data, infrastructure, and governance will become the bedrock of enterprise innovation,” said Manish Gupta, President and Managing Director, Dell Technologies India.