9 months ago
GCCs Embrace AI, But Lack ROI Frameworks, Zinnov-ProHance Study Finds
Imagine many companies, called GCCs, are trying out a new technology called AI.
Most of them, almost all, are either testing it or already using it.
But, here's the tricky part: most of these companies don't have a good way to know if the AI is actually helping them save money or make things better.
It's like giving lots of kids new toys but not checking if they are learning anything from them.
The study suggests that leaders think AI isn't very advanced yet, but the employees using it think it is.
This difference in opinion can slow things down.
To fix this, experts have created a special checklist to help companies measure if their AI is truly working and worth the cost.
This checklist looks at how advanced the AI is, if they can see how it works before and after, how much people are using it, how much it really costs, and what good things it does.
The study also points out that to make AI work well, companies need good data, skilled people, clear rules, and to know how well it's being used.
92% of GCCs in India are actively piloting or scaling AI initiatives.
Over 70% of these GCCs lack structured ROI frameworks to measure AI's impact.
A perception gap exists between leaders who report low AI maturity and employees who show higher proficiency.
The Zinnov-ProHance study proposes an adaptable ROI from AI framework across five dimensions.
Key barriers to scaling AI include fragmented data, skill shortages, weak governance, and poor adoption visibility.
- Who
- Global Capability Centers (GCCs) in India, Zinnov, ProHance
- What
- A study revealing that while 92% of GCCs are piloting or scaling AI, over 70% lack structured ROI frameworks to measure its impact.
- Where
- India
- When
- November 12, 2025
- Why
- To highlight the gap between AI ambition and accountability, emphasizing the need for ROI-first discipline and providing a framework for measurable value.
Key facts
- AI Adoption Rate
- 92% of GCCs piloting or scaling AI
- ROI Frameworks
- Over 70% lack structured ROI frameworks
- Study Participants
- 160+ GCC leaders and employee survey
- Key Barriers to Scaling AI
- Fragmented data, skill shortages, lack of governance, poor adoption visibility
- Framework Dimensions
- Maturity, Baseline Visibility, Adoption Breadth/Depth, Total Cost of Ownership, Value Delivered
Quotes
Karthik Padmanabhan
Managing Partner, Zinnov
“AI adoption in GCCs is no longer the barrier – 92% are already piloting or scaling use cases. The real hurdle is ROI.”
livemint.com
“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.”
livemint.com
Saurabh Sharma
COO, ProHance
“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.”
livemint.com
“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.”
livemint.com
Sources
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