With the rapid maturity of India’s AI landscape, the conversation has decisively shifted from “Should we adopt AI?” to “Are we really seeing returns from it?”
As AI spending accelerates, companies, especially Global Capability Centres (GCCs), are now under growing pressure to convert their investments into measurable business value.
Recently, Accenture reported another record year with $69.7 billion in revenue for FY-25, up 7% from last year. Yet, the optimism around AI appears to be cooling. CEO Julie Sweet acknowledged that the AI boom has yet to deliver on its promise, pointing to job cuts, slower growth guidance, and underwhelming returns from AI deals as key warning signals.
“AI has taken the mind share of CEOs, the C-suite and boards faster than any technology development we’ve seen in the past few decades,” Sweet said. “Yet the financial payoff is lagging.”
This sentiment echoes across the GCC ecosystem. According to a report coauthored by ProHance and Zinnov — ‘Navigating AI ROI – How GCCs Can Unlock Scalable Enterprise Value,’ — 92% of GCCs are already piloting or scaling AI use cases. But the unresolved challenge remains the same: ROI. Nearly 72% of leaders admit they lack a structured ROI framework, leaving investments justified more by promise than by proof.
Talking to AIM, Karthik Padmanabhan, managing partner Zinnov, mentioned that the phase of testing the waters, pilots, and POCs is done now. AI adoption has moved beyond experimentation to full-scale deployment.
“Only about 6% to 8% were in that early evaluation, piloting the POC stage,” Saurabh Sharma, chief operating officer, ProHance, told AIM, emphasising the momentum of AI integration within enterprises.
Yet, despite near-universal adoption, the return on investment remains varied.
Sagar PV, CTO, Mindsprint, a technology firm that specialises in AI-driven solutions, added that for GCCs, the true measure of AI ROI isn’t in short-term cost savings or efficiency metrics; it’s in how deeply AI becomes embedded into business workflows and decision-making.
“Too many investments still chase technology for its own sake. The shift we’re seeing is from deploying AI to demonstrate capability, toward deploying AI to solve real, high-impact problems,” he said.
The ROI Question?
Sharma underscored that defining ROI itself can be complex.Tangible benefits might include productivity or workforce optimisation, while intangible gains could reflect better employee or customer experience.
“In the BPO or the IT industry, it always boils down to… if I’m doing it efficiently, do I need more people or less people now?” he noted.
Sectors like banking remain cautious due to risk sensitivity. This means that while AI deployment is advancing, the path to measurable ROI is slower, requiring oversight, validation, and a strong governance framework.
Sharma noted that while LLMs are claimed to be 92% effective, relying on that level of accuracy in production highlights the delicate balance between innovation and risk management in high-stakes environments.
Talking to AIM, Alouk Kumar, CEO, Inductus Group mentioned about the evolving nature of ROI in GCCs, stating, “Calculating ROI in today’s GCC environment involves much more than conventional cost arbitrage.”
In India, GCCs are increasingly adopting multidimensional ROI frameworks that go beyond simple cost savings. With substantial investments in state-of-the-art facilities, sophisticated campuses, and innovation hubs, these centres now measure ROI across financial, strategic, and operational dimensions.
He added that the real payoff comes from faster go-to-market cycles, improved product quality, data-driven decision-making, and new revenue streams that were previously unachievable in offshore models.
For many global enterprises, the value generated by Indian GCCs now rivals or even surpasses that of primary markets. These centres are increasingly evaluated based on their ability to innovate, collaborate across time zones, and co-create solutions that enhance resilience and long-term competitiveness.
“The true ROI is measured not just in monetary terms, but also in the agility, innovation, and sustainability these GCCs bring to the enterprise ecosystem.” Kumar added.
Perception vs Reality of Adoption
The study also uncovered a disconnect between leadership perceptions of AI adoption and actual usage. Many organisations license AI tools for thousands of employees, but active usage often remains far lower.
As per the report, 63% of GCC leaders continue to face challenges around visibility, measurement, and the true depth of AI adoption. Many lack clear baselines on productivity or capacity, making it difficult to articulate the tangible benefits of AI or any efficiency tool. Most organisations still do not have a real-time, unified view of AI usage across roles or geographies, creating a visibility gap.
This is compounded by the measurement gap as there is no structured model to measure how AI is delivering outcomes. Adoption is often reported, but rarely tied to business results due to inconsistent metrics and missing baselines.
Meanwhile, the proficiency and role enablement gap persists, fewer than 40% of users are proficient in using AI tools. Even though employees get access to tools but lack role-specific playbooks and prompting skills, limiting confidence and deep usage.
Finally, cultural resistance and trust barriers continue to impede progress. Fear of job loss and uncertainty about AI’s impact on roles have created hesitation across the workforce and even among leadership.
Moreover, about 66% of GCC leaders identified data readiness, governance, and infrastructure as major hurdles to realising AI’s full potential. Fragmented datasets and siloed systems continue to obstruct integration and delay access, creating significant data quality and unification challenges.
Compounding these issues are infrastructure scalability gaps, limited compute capacity, legacy systems, and outdated middleware that restrict organisations from operating at AI-ready speed and scale.
In this regard, Monica Pirgal, CEO, Bhartiya Converge, a GCC enablement platform, told AIM, that “For GCCs, the ROI from AI initiatives—both in the short and long term—will be evaluated through measurable outcomes such as cost optimisation, which remain essential.”
However, she added that the broader strategic ROI will be defined through the ‘RIPE’ framework, encompassing revenue generation and risk reduction, innovation, productivity enhancement, efficiency improvement and enhanced customer experience.
Another essential piece of the ROI puzzle is the human in the loop element.
Since “human capital still accounts for 60–70% of the cost,” as Padmanabhan added, organisations must baseline effort levels before and after AI interventions. Comparative analysis between AI-using and non-AI teams helps quantify productivity gains, freeing latent capacity without expanding headcount.
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