India’s GCCs could become agentic AI transformation engines by 2030: Dell-Zinnov report
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India’s Global Capability Centres (GCCs) are entering a new phase in which their ability to scale artificial intelligence (AI) and deliver measurable business outcomes could become more important than the number of AI pilots they run, according to a new report by Dell Technologies and Zinnov.
The report, titled “India GCCs 2030: From Capability Centers to Agentic Transformation Engines”, was released at the Dell Technologies Forum 2026. Based on surveys and interviews with more than 50 senior GCC leaders across sectors including banking, financial services and insurance (BFSI), retail, manufacturing and software, the report highlights the challenges Indian GCCs face as AI moves from experimentation to enterprise deployment.
Nearly 70% of GCCs remain stuck at the pilot stage, the report found. While many centres have AI roadmaps and are experimenting with use cases, fragmented data, legacy technology, governance gaps, security controls and talent models designed for a pre-AI environment are preventing these initiatives from moving into sustained 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. The GCCs that build these capabilities now will define how their organizations harness AI globally, and Dell Technologies is focused on enabling that journey from foundation to transformation,” said Manish Gupta, President and Managing Director, Dell Technologies India.
India currently has more than 2,100 GCCs employing around 2.36 million people and generating $98.4 billion in revenue in FY26, according to the report. Around 70% of GCCs have a defined AI roadmap or charter, while more than 1,200 centres have built AI and machine learning capabilities. The report also found that 64% of GCC leaders hold dual global mandates, running their India centres while also owning a global function. Meanwhile, 66% of GCC leaders rank top-line business impact as a high priority for their enterprise AI strategy, indicating a shift in the role GCCs are expected to play.
AI is forcing GCCs to rethink infrastructure and workforce
The report said the maturity curve for GCCs is becoming shorter, with 27% of new GCCs now reaching Portfolio Hub maturity within five years, compared with nearly a decade historically. At the same time, AI mandates are arriving earlier in the GCC maturity journey, leaving centres less time to build the infrastructure, data and governance required to support them.
The scale of AI workloads is also changing the economics of technology deployment. According to the report, agentic AI workflows can consume between 10,000 and 500,000 tokens per workflow, compared with around 1,000 to 2,000 tokens for a standard chat interaction. This makes early decisions around compute, infrastructure, security and workload architecture increasingly important as AI moves into production.
The report recommends that GCCs make infrastructure decisions based on the nature of their workloads. Sensitive data, regulatory requirements, business-critical processes and high, predictable usage may require greater infrastructure control, while lower-risk or experimental workloads can be handled through leased or managed environments. The report also proposes a “Sovereign Sandbox” model that would allow GCCs to experiment with regulated or proprietary data in a controlled environment before moving those workloads into production.
Beyond technology, workforce redesign is expected to become a major priority. The report estimates that around 55% of routine GCC work is exposed to AI-led automation, while 60% of the workforce could require reskilling by 2030. “The GCC model is reaching an inflection point. For the last two decades, the conversation was largely about scale, talent, and capability. The next decade will be about ownership. As AI and agentic systems become embedded into enterprise workflows, GCCs will increasingly be expected to own products, platforms, markets, and measurable business outcomes. Those that build the right data, technology, governance, and talent foundations now will move from being capability centres to becoming true transformation engines for the enterprise,” said Sidhant Rastogi, President, Zinnov.
By 2030, the report argues, the GCCs that emerge as strategic transformation engines will be those that can move beyond AI experimentation and integrate agentic workflows into core business functions while maintaining the data, infrastructure, governance and talent required to operate them at scale.