Based on insights from 160+ GCC leaders and an employee survey, the study contrasts leadership priorities with workforce realities in AI adoption.
Leaders report limited AI adoption and low skills maturity, while employees show higher proficiency and frequent use. This perception gap is more than cultural; it is a structural blind spot that can slow scaling and undervalue real productivity gains at the grassroots.
Reframing ROI through a Pragmatic Evaluation Lens
The study finds ROI is the most urgent challenge today. Pilots are rising, but without structured measurement, leaders can’t prove value. Without ROI clarity, AI risks staying an experiment instead of becoming a lasting enterprise enabler.
To address this, Zinnov and ProHance introduced the ROI from AI framework to bring discipline and credibility to measurement. The framework is not a one-size-fits-all formula but an adaptable guide that helps leaders evaluate ROI based on their industry, maturity, and organizational context.
The framework evaluates ROI across five dimensions:
- Stage of maturity – from pilot to enterprise scale
- Baseline visibility – before-and-after measurement with attribution
- Adoption breadth and depth – tracking workflow integration beyond licenses
- Total Cost of AI Ownership – including hidden costs such as governance and compliance
- Value delivered – capturing both tangible gains (efficiency, productivity, compliance) and intangible outcomes (employee and customer experience)
By using this lens, GCC leaders can measure outcomes credibly, align adoption strategies with business priorities, and make scaling decisions with confidence—addressing the ROI problem head-on.
Four Pillars of Readiness
The whitepaper shows that scaling AI is less about technology maturity and more about operating model readiness across four key pillars.
1- Data & Infrastructure – 66% of leaders cited fragmented data, poor integration, and compliance risks as barriers. Unified, secure platforms are critical to scale.
2- Talent – 47% flagged skill shortages and low fluency; domain-specific, role-based skilling is essential to position AI as augmentation, not replacement.
3- Governance & Change – 55% of GCCs lack structured governance, weakening accountability. Embedding clear ownership and proactive change management is essential for trust.
4- Adoption & Usage Depth – 63% of leaders lack visibility into adoption, even as employees report frequent use. Measuring real workflow integration and impact is key to credible ROI.
“AI adoption in GCCs is no longer the barrier – 92% are already piloting or scaling use cases. The real hurdle is ROI.” Said Karthik Padmanabhan, Managing Partner, Zinnov. “Leaders tell us pilots often multiply without proving business impact, governance remains inconsistent, and costs are routinely underestimated. This creates a widening gulf between AI activity and measurable value. The true test of AI is not in the number of pilots, but in outcomes that truly matter – accelerated cycle times, fewer errors, empowered employees, and differentiated customer experiences. Through this study, we have given leaders a pragmatic framework, grounded in four readiness pillars, to evaluate and unlock ROI at scale, moving AI from experimentation to a trusted Enterprise capability.”
“GCC leaders are not short of ambition when it comes to AI, but without a credible adoption and ROI framework, that ambition risks getting trapped in pilot purgatory,” said Saurabh Sharma, COO, ProHance. “At ProHance, we see every day how visibility into work, coupled with the depth and breadth of AI adoption, directly impacts productivity outcomes. This whitepaper is about moving AI from experimentation to enterprise impact – helping GCCs not just deploy AI, but derive sustained, measurable returns that strengthen both business performance and employee outcomes.”
AI’s decisive moment for GCCs is here. Success depends on measurable ROI, readiness across four pillars, and disciplined scaling. The next generation of GCC leaders will measure early, close perception gaps, and embed AI as a lasting enterprise capability.
Download the Whitepaper here
About Zinnov
Founded in 2002, Zinnov is a global management and strategy consulting firm, with presence in New York, Santa Clara, Houston, Seattle, Bangalore, Gurgaon, Hyderabad, Pune, London and Paris. Over the past 23 years, Zinnov has successfully consulted with over 250+ Fortune 500 enterprises to develop actionable insights to help them accelerate their technology journeys to create value – across dimensions of revenue, transformation, and optimization. For more information, visit http://www.zinnov.com
About ProHance -
ProHance is a next-gen, AI-led workforce management platform built on first principles. It empowers over 400,000 users across 36 countries, helping Fortune 500 enterprises, shared services, and GCCs gain real-time visibility, improve productivity, and drive measurable value in digital and hybrid environments.
It delivers real-time insights into workforce utilization and capacity, optimizes end-to-end processes, and leverages advanced analytics and AI to enhance decision-making. Through its AI-powered Retention Risk Index (RRI), ProHance benchmarks workforce stability and engagement while enabling scalable AI adoption to unlock sustainable ROI and enterprise-wide transformation.
For more information, visit www.prohance.net or follow us on LinkedIn
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