After reporting just 0.9% year-on-year (YoY) growth in IT services revenue and an operating margin that slipped to a 15-quarter low of 16%, Wipro’s post-earnings discussion was dominated not by the numbers, but by its artificial intelligence ambitions.
At the IT major’s post-earnings interaction, CEO Srini Pallia repeatedly described Wipro as a “consulting-led, AI-powered” organisation, underscoring how deeply AI is shaping the company’s positioning, client conversations and future roadmap.
If the management commentary is any indication, AI has moved from being a technology opportunity to becoming the defining theme of Wipro’s transformation strategy.
Wipro’s four bets
Pallia broke the strategy down into four pillars.
First, an AI-native business focused on building new industry platforms from scratch, spanning sectors such as healthcare and transportation, while also modernising Wipro’s legacy platforms with AI capabilities. The team is also working with partners to develop small language models (SLMs) tailored for specific industries.
Second, the Wipro Innovation Network, a network of ten hubs around the world where Wipro co-creates AI solutions with clients. Agentic AI is the primary focus, although the company is also exploring quantum computing and space technology.
Third, partnerships with leading AI labs, applied one industry at a time. Pallia pointed to recent wins as evidence the strategy is gaining traction. Capco, Wipro’s BFSI consulting arm, received an AI Governance and Risk Excellence Award at the OpenAI Partner Summit, while Wipro’s UK AI Lab won an OpenAI hackathon.
Fourth, Wipro Ventures, a $500 million fund that has been investing in AI, data and cybersecurity startups. Pallia said the fund is about more than financial returns. It gives Wipro early access to emerging technologies while helping promising startups, which often struggle to enter large enterprises on their own, reach Wipro’s global client base.
Why Wipro isn’t putting all its eggs in one basket
One of the sharper questions during the interaction centred on geopolitics. Access to some frontier AI models has recently become subject to export controls, prompting a question on whether that makes Wipro’s AI partnerships risky.
Pallia’s response was straightforward: diversification is precisely the strategy. Clients, he said, need the flexibility to choose between premium frontier models and lower-cost open-source alternatives, depending on the complexity of the task, especially as token costs continue to rise.
He also pointed to Wipro’s Applied AI Centre of Excellence (CoE) for Claude models, through which the company is training 10,000 employees on Anthropic’s AI models, as part of the same strategy.
Also Read: Why Wipro’s margins fell to a 15-quarter low and when they may recover
Combined with its partnership with OpenAI, Pallia’s broader point was that building deep capabilities across multiple AI providers, rather than relying on a single model, allows Wipro to continue advising clients regardless of which models are available or commercially viable. Model release cycles, he noted, have already shortened from months to weeks.
What the AI work actually looks like
Much of Wipro’s client-facing AI work now runs through its Wipro Intelligence platform suite, with sub-platforms WINGS and WEGA driving many of its enterprise AI deployments.
Among the examples cited were an AI-powered command centre built for a European specialty chemicals company, a multi-agent system for a healthcare client that reduced provider-enrolment processing time by up to 70%, and an overhaul of pharmacovigilance operations for a life sciences client using autonomous AI agents.
Another emerging theme was AI data centres. Pallia said Wipro is increasingly being asked to design, build and manage AI data centres for clients, alongside growing opportunities in sovereign AI, as governments place greater emphasis on data localisation and secure infrastructure.
The number Wipro won’t give
When asked the obvious question—what proportion of revenue now comes from AI—Pallia declined to disclose a figure, even as some competitors have started providing such metrics.
He compared the current AI wave with the earlier digital transformation era, when many companies claimed the majority of their revenue came from “digital”, making the metric increasingly meaningless.
Instead, he argued that AI is now embedded across almost every aspect of Wipro’s business—from infrastructure management and software development to consulting and business transformation—making it difficult to isolate as a standalone revenue stream. Rather than focusing on an AI revenue percentage, Pallia said the company prefers to measure the business value delivered through each AI engagement.
The same approach extended to workforce disclosures. When asked about the number of forward-deployed engineers (FDEs), a role drawing increasing attention across the industry, Chief Human Resources Officer Saurabh Goyal said Wipro does not disclose a separate FDE headcount, as AI capabilities are now spread across the broader workforce rather than confined to a specialised group.
The catch
For all the optimism around AI, Pallia acknowledged an important near-term challenge. Much of the current deal pipeline continues to be driven by cost optimisation and vendor consolidation, with many clients reallocating existing technology budgets towards AI rather than committing fresh spending.
He noted that while nearly 75% of CEOs are now directly involved in AI investment decisions, chief financial officers remain cautious about balancing rising token costs against measurable returns. Pallia expects that dynamic to ease over the coming quarters, much like digital transformation spending eventually did.
His message was clear: AI is expanding the addressable market for IT services rather than shrinking it. In his view, companies with capabilities spanning the broader AI ecosystem—rather than those tied to a single model or provider—will be best positioned to capture the next wave of enterprise technology spending.
