With up to half of customer-service interactions carrying the potential for self-service, multinational companies are turning to their India GCCs to move AI beyond scattered chatbots and into the core of global customer operations.
According to a recent analysis by EY India, as much as 40–50% of customer-service interactions have self-service potential through chatbots or intelligent virtual assistants, while AI could automate about 20–30% of an agent’s workload.
However, unlocking those gains will require more than adding AI tools to existing contact centres, said Preeti Anand, partner, business consulting, customer service transformation at EY India, and author of the report.
“Capturing either tier at scale is an operating model problem, not just a technology one,” Anand wrote. Enterprises require a clear customer-service AI strategy, centralised governance and defined ownership if agentic AI is to evolve from isolated deployments into an enterprise capability, she added.
From chatbots to autonomous service
The transition marks a shift from AI-assisted automation—such as call summarisation, after-call documentation and next-best-action recommendations—to AI-led journeys. In the latter model, AI agents can interpret intent, retrieve information across enterprise systems and act across front-, middle- and back-office workflows.
For instance, an AI system could identify a service failure, assess the value and history of the affected customer, and initiate a retention offer. Human agents would increasingly focus on sensitive cases, exceptions and interactions requiring empathy or judgement.
Most enterprises, however, continue to operate layered service models in which basic queries are routed through interactive voice response systems or static knowledge bases, while AI is added as a separate technology layer. Fragmented delivery across markets also results in regions deploying their own processes, data and tools, limiting consistency.
Anand said GCC-led customer-experience centres of excellence can address this gap by assuming central ownership of service design, AI deployment, knowledge management and governance. In this model, routine queries are handled through intelligent virtual assistants, while employees supported by AI manage complex or sensitive cases.
The GCC can also integrate AI with customer relationship management, ticketing and service platforms, providing a unified customer view that may be difficult to achieve through disconnected, market-level deployments.
This represents a departure from conventional outsourcing arrangements built around interaction volumes, capacity and service-level agreements. Such contracts can offer limited incentives to automate interactions or redesign customer journeys because reducing contact volumes may conflict with the underlying commercial model
The report cited an unnamed technology conglomerate with more than 35,000 customer-service agents that made its India-based CX centre of excellence the central hub for AI-native service. The programme reduced agent coordination time by about 13%, cut chat-handling time by up to 16% and lowered manual effort by roughly 80% in select processes.
India’s GCC advantage
India has close to 600,000 AI-native customer-experience professionals, accounting for about 16% of the global talent pool, EY estimated. The country also hosts more than 500 AI-led CX platform companies and offers operating costs roughly three to five times lower than other markets.
AI investment is already accelerating. The EY India GCC Pulse Survey published last year, found that 83% of Indian GCCs were investing in generative AI and 58% in agentic AI. Customer service was the leading GenAI use case, cited by 65% of respondents, while 67% had established dedicated innovation teams or incubation programmes.
The shift will also change how GCC performance and talent are measured. “As AI agents take on a larger share of operational work, GCCs will increasingly evolve into AI command centres responsible for designing, deploying and governing intelligent systems at scale,” Karan Dhundia, regional managing principal at consulting firm ZS, said in an earlier interview.
According to Dhundia, performance metrics will move beyond headcount, cost per employee and service-level compliance towards autonomous task-completion rates, AI deployment speed and the effectiveness of human-AI collaboration. Talent demand will correspondingly shift towards AI orchestration engineers, governance specialists and data architects.
For CIOs and GCC leaders, the next phase will therefore be less about deploying another chatbot and more about deciding who owns the customer journey, the underlying data and the actions AI is permitted to take. GCCs that secure that mandate could move from supporting global customer operations to actively shaping them.
Global Capability CentresGCCs in Indiaartificial intelligenceAgentic AIgenerative AIAI-native customer servicecustomer experiencecustomer service automationAI Centres of ExcellenceEnterprise AIAI governanceHuman-AI CollaborationIndia GCC EcosystemEY IndiaAI talentdigital transformation
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