Indian information technology companies have spent the past two years talking about artificial intelligence replacing tasks, lifting productivity and creating new business opportunities. Wipro now says many companies are running into a different hurdle as they prepare AI for wider use, pointing to a challenge that is receiving growing attention across the IT services industry.
The issue, Wipro Chief Executive Officer Srini Pallia said, is not about access to AI models or computing power. Instead, companies are finding that preparing their organisations for AI requires answering questions they had not considered before.
Speaking during the company’s June-quarter earnings call, Pallia said many enterprises are struggling with data as they move from experimentation to deployment.
“Some enterprises have told us we’ve got too much of data. We don’t know whether do we need all this data to get the AI right,” Pallia said.
He said organisations are increasingly seeking help with what Wipro calls “data priming for AI”, alongside services such as AI advisory, agent deployment and AI security.
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Industry Trend
While Wipro’s observation was the most direct, similar themes emerged in earnings calls by other large Indian IT companies this week.
HCLTech said enterprises are increasingly building AI systems around their own data rather than relying entirely on public AI models. The company said clients are looking at smaller language models trained on enterprise data and described data preparation as a growing opportunity as organisations build AI stacks.
Tech Mahindra also said customer discussions are moving beyond AI pilots towards data modernisation, governance, operating models and managing AI costs as companies try to deploy the technology across their businesses.
Tata Consultancy Services similarly identified AI-led transformation, platform rationalisation, sovereign cloud and vendor consolidation as key priorities for clients, suggesting that enterprise AI conversations are increasingly centred on building the right foundations rather than simply adopting new models.
Beyond Models
Pallia said companies are now weighing a broader set of decisions as AI projects expand, including how AI agents should be managed, how different AI models should be deployed and whether the returns justify the costs.
He said finance chiefs are increasingly asking which models deliver the best return on investment for different business processes, while demand is also rising for services around AI governance, security and responsible deployment.
Despite those challenges, Pallia said Wipro sees the changes creating new opportunities for IT service providers as companies move from testing AI tools to integrating them into day-to-day operations.
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