GCCs in India evolve into AI and product innovation hubs

Global Capability Centres (GCCs) in India are transforming from cost centers focused on service delivery into hubs for product development, innovation, and AI-driven solutions. Kewyn George, an AI and GCC leader, shared insights on this shift at DevSparks Chennai 2026, highlighting how automation, changing developer roles, and AI adoption are reshaping these organizations.

GCCs Shift from Service Delivery to Product Innovation

Global Capability Centres (GCCs) in India are undergoing a significant transformation, according to Kewyn George, an AI and GCC leader. Speaking at DevSparks Chennai 2026, George noted that these centers are evolving from cost-focused service delivery hubs into centers for product development, innovation, and AI-driven solutions.

Automation and End-to-End Product Ownership

George highlighted that this shift is being driven by widespread automation of repetitive tasks. He estimated that 50-60% of GCCs are now automating high-volume work, such as service desk tickets and similar processes. This automation is freeing up resources for more strategic initiatives, including end-to-end product development.

For example, some GCCs are now responsible for developing entire systems, such as credit management platforms for banking clients. This marks a departure from their traditional role as support functions.

AI Adoption and the Risk of the 'Pilot Graveyard'

AI adoption in GCCs is accelerating, fueled by fear of missing out (FOMO) among multinational companies and GCCs themselves. According to George, AI use cases in GCCs fall into two categories: those directly tied to revenue growth and those aimed at improving internal productivity.

However, George warned of the "pilot graveyard"—a term for proofs of concept and hackathon projects that initially gain traction but are ultimately abandoned. This phenomenon underscores the need for GCCs to align AI initiatives with clear business outcomes to ensure scalability and impact.

Changing Developer Roles and Skill Gaps

The transformation of GCCs is also reshaping developer roles. George emphasized that engineers can no longer afford to passively wait for requirements. Instead, they must proactively engage with business and customer teams to identify problems and opportunities.

He categorized developers into three generations based on their training: those trained on legacy systems, those who learned Java or similar languages, and those who began coding with AI tools. This generational divide reflects the evolving skill sets required in modern GCCs.

The Rise of AI Engineering and Talent Challenges

AI engineering is emerging as a critical discipline within GCCs, but it demands more than just technical expertise. George noted that successful AI engineers must combine product knowledge, process knowledge, business acumen, and technical skills.

This shift has implications for hiring and talent development. George estimated that only about 30% of engineering graduates may secure strong roles in GCCs, as automation reduces the need for routine, manual tasks. The gap between high-performing engineers and the rest could widen, making upskilling a priority for both individuals and organizations.

What this means

Lazyfounder analysis — our interpretation, not reported fact.

The transformation of GCCs in India reflects a broader industry shift toward integrating AI and product-driven innovation into traditional service models. For founders and operators, this means recalibrating hiring strategies to prioritize engineers who can bridge technical and business gaps—those who understand not just how to build, but what to build and why.

The risk of the "pilot graveyard" is particularly relevant: without clear pathways to scale, even promising AI proofs of concept can stall. GCCs—and the startups emulating their models—must align AI initiatives with measurable outcomes, whether revenue growth or operational efficiency.

For engineers, this shift demands adaptability. Legacy skills alone won’t suffice; familiarity with AI tools and business acumen are becoming table stakes. Meanwhile, the automation of routine tasks could widen the gap between high-performing engineers and the rest, making continuous upskilling critical.

Key takeaways

• GCCs in India are evolving from service delivery centers to product and AI innovation hubs, driven by automation and AI adoption.
• Repetitive tasks like service desk tickets are being automated in 50-60% of GCCs, reducing manual workloads.
• AI use cases in GCCs are split between revenue-focused initiatives and internal productivity improvements.
• The "pilot graveyard" phenomenon highlights the risk of abandoned proofs of concept and hackathon projects.
• Developers must proactively engage with business teams to identify problems, rather than waiting for formal requirements.
• AI engineering demands a mix of product, process, business, and technical knowledge, not just coding skills.
• Automation may limit strong GCC roles to only about 30% of engineering graduates, emphasizing skill gaps.

FAQ

What are GCCs, and how are they changing?

Global Capability Centres (GCCs) are offshore units set up by multinational companies to handle specific functions like IT, finance, or customer support. Traditionally, they focused on cost-effective service delivery. Now, many GCCs in India are evolving into centers for product development, innovation, and AI-driven solutions.

What is the 'pilot graveyard'?

The 'pilot graveyard' refers to proofs of concept, hackathon projects, or pilot initiatives that are abandoned after initial excitement. These projects often fail to scale or deliver measurable outcomes, becoming a missed opportunity for innovation.

How is AI adoption impacting developer roles in GCCs?

AI adoption is requiring developers to take a more proactive role in identifying business problems and opportunities. Engineers must now combine technical skills with product, process, and business knowledge, rather than just executing predefined requirements.

Why are only 30% of engineering graduates expected to secure strong roles in GCCs?

Automation is reducing the need for manual, repetitive tasks, which were traditionally handled by entry-level engineers. As GCCs prioritize AI-driven innovation and product development, they seek engineers with advanced skills, leaving fewer strong roles for those without specialization.

What skills are required for AI engineering in GCCs?

AI engineering in GCCs requires a combination of technical expertise, product knowledge, process understanding, and business acumen. Developers must understand not just how to build solutions, but also how they fit into broader business goals.

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