80% of Indian enterprises invest in AI for growth, but only 12% can measure returns
Four out of five Indian enterprises are investing in AI and technology primarily to drive revenue growth, yet only one in eight can comprehensively measure what those investments are returning, according to a recent study commissioned by Cognizant and Dun & Bradstreet.
The survey of 105 senior business and technology leaders across banking, manufacturing, pharmaceuticals and Global Capability Centres found that 80% of organisations prioritise technology investments for revenue growth, while only 12% have a fully consolidated, enterprise-wide view of technology spending needed to accurately measure returns.
Fragmented technology data remains the biggest obstacle to effective AI and IT cost governance, cited by 63% of respondents. Visibility is strongest for cloud services and software licences but weakest across infrastructure, labour and end-user devices, making end-to-end ROI difficult to quantify.
Budgeting practices are compounding the challenge. Nearly two-thirds of respondents said rigid budgeting cycles prevent organisations from reallocating spending towards higher-value AI initiatives as business priorities change during the year. Only about half reported having a formal process for shifting technology investments quickly enough to capture emerging opportunities.
The findings mirror a broader global trend.
A separate Economist Enterprise study, supported by HCLTech, surveyed 202 C-suite executives across technology, media and telecommunications companies in the US, UK, Ireland and the Benelux region and found a similar disconnect between AI investment and measurable business outcomes. While 90% of executives said they were satisfied with their AI investments, fewer than one-third had a framework capable of measuring AI’s commercial impact. More than half reported significant AI spending but only limited measurable returns in commercial and revenue management, the business function where AI is expected to deliver the greatest growth.
Despite examining different markets, the two studies point to the same conclusion that enterprise confidence in AI is outpacing the ability to measure its financial impact.
The research also suggests that the organisations generating the strongest returns are taking a more disciplined approach. According to research cited in the Economist Enterprise study, companies concentrating AI investment on a smaller number of high-value use cases generate roughly twice the returns of those spreading investments across multiple initiatives.
In India, some of the clearest evidence is emerging from leading Global Capability Centres. The study found that advanced GCCs adopting a “Digital Tech Equivalent” operating model, combining around 40% human oversight with 60% autonomous agentic capacity, are reporting long-term operating cost reductions of between 25% and 40%, achieved through productivity gains rather than workforce reductions.
Researchers behind both studies argue that improving AI ROI will require enterprises to move beyond periodic reviews of technology spending towards continuous, real-time measurement of AI performance. That includes tracking whether productivity gains are translating into lower operating costs or higher revenue, alongside closer collaboration between finance and technology teams to improve governance and investment decisions.
The findings suggest the next phase of enterprise AI adoption will not be defined by how much organisations spend, but by how effectively they can measure, govern and monetise those investments. For enterprises racing to deploy AI at scale, proving return on investment may soon become as important as the investment itself.
