Navigating AI ROI: How GCCs Can Unlock Scalable Enterprise Value

AI adoption across GCCs has crossed a decisive threshold. 

92% of GCCs in India are now piloting or scaling AI use cases. Yet, despite this remarkable momentum, over 70% of leaders admit they lack a structured ROI framework to measure success. 

This imbalance between enthusiasm and accountability has created a growing divide, a gap between AI effort and measurable return. 

Projects multiply, dashboards look impressive, but tangible business outcomes remain elusive. Without clear baselines, attribution, or alignment on what “value” really means, leaders are unable to prove ROI or make confident scaling decisions. 

Why This Matters Now

Indian GCCs are uniquely positioned to lead enterprise AI transformation, as orchestrators, incubators, and stewards of governance. But ambition has outpaced measurement maturity. AI can no longer be justified by promise; it must be proven through evidence. 

To avoid the pitfalls seen in Cloud’s slow adoption and RPA’s hype-driven stagnation, GCCs must ground their AI strategies in measurable outcomes, faster cycle times, fewer errors, empowered employees, and better customer experiences. 

That’s why Zinnov and ProHance co-developed “Navigating AI ROI: How GCCs Can Unlock Scalable Enterprise Value”, a whitepaper designed to close the ROI gap and bring discipline to scaling. 

Grounded in inputs from 160+ survey responses from leaders and employees, and 50+ hours of leader interviews across industries, this study provides a dual-lens perspective, capturing both leadership intent and on-ground realities of AI adoption. It brings to light the perception gap between leadership intent and employees’ real-world AI usage and impact, revealing how limited visibility and inconsistent measurement hinder scaling. The findings reinforce the need for a unified Value Scorecard that captures inputs, throughputs, outcomes, and impact metrics to drive evidence-based scaling.

What You’ll Learn 

Discover how GCCs can shift from experimentation to enterprise-scale impact through: 

• Zinnov’s structured approach to move beyond fragmented metrics and measure AI’s value with discipline and credibility. 

• How ProHance’s analytics enable real-time, workflow-level measurement of adoption and performance. 

• The foundational levers, Data, Talent, Governance & Change, and Adoption Depth, that determine scalable AI success. 

• Real examples from leading GCCs turning AI pilots into proven value.

Together, these insights form a clear roadmap for GCC leaders to close the ROI gap and build AI as a sustained enterprise capability, grounded in data, not just ambition. The age of “AI experimentation” is ending. The next chapter belongs to those who can measure early, scale confidently, and lead with clarity.  

Download the Whitepaper and start your journey from AI ambition to AI impact with Zinnov’s framework on AI transformation and leveraging actionable AI-blueprint that enables scalable, enterprise-wide AI adoption.

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