In Brief

India’s Global Capability Centres (GCCs) are rapidly transitioning from cost-driven service units to strategic hubs of innovation, engineering, and R&D. As digital acceleration reshapes enterprise priorities globally, the ability to attract deep-skilled talent and sustain innovation has become a key differentiator for high-performing GCCs.

This report presents a detailed analysis of how industry–academia alliances can solve the talent readiness gap, embed innovation at scale, and establish India’s GCCs as global powerhouses—not just of delivery, but of capability creation.

Crafted by domain experts and enriched with real-world case studies, this document provides CXOs, innovation heads, and ecosystem leaders with actionable frameworks to future-proof their GCC strategies.

Overview

This report examines the strategic significance of industry–academia collaboration in unlocking the next phase of GCC growth in India. Key themes include:

• The evolution of India’s GCCs from operational hubs to innovation centers
• Talent shortages and the widening skills gap in AI, ML, cloud, and cybersecurity
• High-impact models of industry–academia alliances: co-developed labs, curriculum co-creation, joint R&D initiatives
• Comparative case studies from global enterprises like Wipro, TCS, Infosys, and Boeing
• Policy recommendations and frameworks to institutionalize academia–industry linkages

Key Highlights

• 90% of Indian GCCs now support end-to-end product and R&D capabilities—yet innovation output remains inconsistent without strategic academic alignment.
• Over 40,000 open roles in cybersecurity were recorded in 2023, despite India producing 800,000+ tech graduates—highlighting the gap between education and employability.
•  Joint R&D labs between GCCs and premier institutions like IITs and IIITs have led to patents, prototypes, and accelerated IP creation across AI, IoT, and next-gen analytics.
• Mid-sized GCCs in Tier-2 cities are leveraging university partnerships to bootstrap innovation capabilities without the overhead of large-scale R&D investments.