AI-First GCCs in India: Why US Firms Are Moving Beyond Outsourcing

by Davis Chackkunni | October 03, 2025

The old outsourcing model made sense when cost-cutting was the only goal. But now, engineering speed, IP ownership, and AI innovation are non-negotiable. That’s why US companies are looking to set up AI-first Global Capability Centers (GCCs) in India, not just to outsource, but to build and scale smarter. With India's GCC market projected to grow to $110 billion with 2400 centers by 2030, the nation has become a powerhouse of innovation.


Outsourcing India GCCs

Source: Ernst and Young

India’s state-of-the-art GCCs offer control that traditional vendors can’t. They give enterprises direct oversight of teams, processes, tools, and outcomes. In addition, they ensure intellectual property is protected and compliance is embedded, guaranteeing a faster pace and greater competitive advantage. 

GCCs in India Have Evolved Radically

India’s GCCs have become centers of innovation, not just execution. The ecosystem is now deep: over 1,800 centers employing more than 1.9 million professionals. These teams aren’t back-office; they’re product designers, AI engineers, IoT architects, and data scientists. According to a recent report, GenAI and related skills see the highest growth at 32% in Indian GCCs. 

Many US-based companies are turning to Indian GCCs to deploy generative models to enhance customer experience, speed testing, and automate complex workflows. AI is pivotal in accelerating GCCs' maturity, with more than 90% of leading GCCs launching or expanding AI-focused centres of excellence over the last year and a half. 

These centres are no longer limited to experimental projects; they are now deeply embedded in operational workflows, unlocking new efficiencies and enabling enterprise-wide innovation. So, what makes India such a sought-after destination? Here are some reasons: 

  • From Outsourced to Owned: When enterprises own their capability centers, they remove third-party dependencies. There is no vendor lock-in, hidden bottlenecks, or waiting for change requests. No hidden bottlenecks. Take Dai-ichi Life, for instance. It is establishing a GCC in Hyderabad focusing on advanced analytics and AI. Or look at Cargill, which is scaling down outsourcing and adding 500 new tech roles in its India GCCs over the next 36 months. Their goal: reduce outsourced tech from 80% to 40% and internalize product capabilities.
  • Large Pool of Talent that is Constantly Growing: India’s tech talent density is unmatched. Over 120,000 professionals are trained in AI and ML, and more than 180 AI/ML Centers of Excellence operate across major cities. With leadership roles shifting, more engineering and product heads reside in India than ever, making the nation a desirable destination for growth and innovation. 
  • AI, IoT, and Product Engineering, all Under One Roof: AI-first GCCs in India don’t just offer talent. They offer the convergence of AI, IoT, and agile product engineering. When these functions live under one roof, innovation accelerates. Teams work cross-functionally, and firmware, software, analytics, and UX evolve together. SAP, for example, launched its Joule AI assistant from its India GCC. This was more than a prototype. It was full-scale engineering, R&D, and go-to-market—all rooted in a single capability hub.
  • Scaling Without Waiting on Vendors: One of the biggest wins of India’s AI-first GCC model is flexible, vendor-free scaling. India’s GCCs help global companies scale without issue; from multiplying data science teams to spinning up new automation pods, and expanding DevOps to 24/7: Indian GCCS allow all this and more. This is particularly valuable for fast-growing companies that seek breathing room and control, need to move fast, and require the freedom to pivot when required.
  • A Culture Shift from Execution to Ownership: Indian GCCs operate as valid extensions of the core business. They take accountability for outcomes, handling roadmap evolution, platform architecture, compliance, and cybersecurity with finesse. These internal engines of delivery and innovation future-proof American enterprises against vendor risk, IP loss, and slow decision cycles.

Moving Beyond Outsourcing: The Indian GCC Edge

GCCs in India aren’t just replicating what works elsewhere. They’re creating solutions that get scaled back to the business. They are building for local complexity, then adapting it for global markets. Whether you want to develop IoT systems and transform them into fleet analytics platforms in the US or establish an AI-based testing automation center that can run across global product teams, Indian GCCs offer all this and more. 

However, GCCs are not plug-and-play. They require the right partner, governance model, talent strategy, and tech stack. When done right, they can transform any business. If done wrong, they become cost centers with no agility. 

At Gadgeon, we help enterprises build and run AI-first capability centers in India, from IoT-enabled innovative systems to AI-driven healthcare and industrial platforms. Whether through Build-Operate-Transfer models or embedded product teams, we prioritize ownership, speed, and scalability.
If you still view India as an outsourcing hub, you’re missing the point. GCCs here now drive strategy, build platforms, and shape IP. They reduce risk, accelerate time to market, and give control back to the enterprise.

The best US companies already know this. They’re not outsourcing; they’re building, in India, with intention.

FAQs

  • What is an AI-first Global Capability Center (GCC)?

An AI-first GCC is a company-owned center focusing on advanced functions like AI/ML, IoT, and product engineering, rather than traditional support or outsourced services.

  • Why are US companies shifting from outsourcing to GCCs in India?

US firms seek greater control over talent, IP, and innovation. Indian GCCs enable faster product development, reduce vendor dependency, and allow scalable, in-house capabilities.

  • How do GCCs help accelerate AI product development and integration?

GCCs allow AI and IoT teams to work closely with product and engineering functions, speeding up prototyping, integration, and testing, without external delays or vendor bottlenecks.


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