Bridging the AI ROI Gap: GCCs' New Framework for Sustainable Value

A joint study by Zinnov and ProHance highlights the disconnect between GCC leaders and employees on AI adoption. While initiatives are widespread, structured ROI frameworks are lacking. The study introduces a new adaptable framework to measure ROI, emphasizing readiness across four key pillars to ensure scalable AI integration.

A recent study by Zinnov and ProHance has identified a significant disconnect between leadership and workforce perspectives on AI adoption in Global Capability Centers (GCCs). Despite 92% of GCCs in India piloting or scaling AI initiatives, over 70% lack the structured frameworks necessary to measure their impact effectively.

Drawing on insights from more than 160 GCC leaders, the study underscores a crucial structural gap in AI readiness. Leaders report limited AI uptake and skills maturity, contrasting with employees who display higher proficiency and frequent use. This perception gap might slow AI scaling and productivity gains.

The study presents a comprehensive framework to bridge this gap by evaluating ROI across five dimensions, from maturity stages to delivered value. It also emphasizes leadership readiness across data infrastructure, talent, governance, and adoption—marking a decisive moment for AI's impact on enterprise capability.

(With inputs from agencies.)