Indian IT's Biggest AI Partners are Also Its Newest Enterprise Threats
By Ajay Rag ·
India’s $280 billion IT services industry is going through some tumultuous times. The release of Claude Code in February sent IT stocks into a free fall, with the Nifty IT index still down 23% year-to-date, wiping out roughly $70 billion in market capitalisation in a matter of weeks.
IT services firms have historically dominated enterprise implementation. But now, Anthropic and OpenAI have launched competing billion-dollar joint ventures designed to embed AI systems directly into enterprise operations.
India’s major IT services firms are now realising that if they can’t beat the AI giants, they must join them.
Infosys, for instance, partnered with Anthropic in February to build AI agents for telecom and banking, and has separately announced a collaboration with OpenAI. TCS, meanwhile, is building AI-optimised data centres with OpenAI as anchor tenant for Stargate India.
But should IT firms be legitimately threatened by AI giants moving into their stronghold of enterprise solutions? Analysts note that forming joint ventures means that AI labs cannot deliver enterprise AI on their own.
"What this proves is that native AI companies also need to build services around AI products or solutions. They cannot remain pure-play AI solutions only," Gaurav Vasu, Founder and CEO of research and consulting firm UnearthInsight, tells AIM. "This validates that services companies, whether consulting services, technology services, or engineering services, are still relevant and still important."
Collaborations are reflected in the announcements. Anthropic’s venture documentation names Deloitte, Accenture, and other consulting firms as partners. Earlier, Anthropic had also partnered with technology firms, embedding Claude into technology services and consulting.
“I think it's very important for these services companies to be very thick with some of these platform companies, because the capabilities are getting unleashed from these platforms,” observes Praveen Bhadada, CEO and MD of consulting firm Neovay Global. “It's in their interest for services companies to know these capabilities and then leverage them for a three-part transformation—protect your current business, launch newer services, and then drive towards outcomes.”
The Venture Model
The AI giants are largely reliant on venture capital to fuel their enterprise ambitions.
Anthropic’s enterprise-focused joint venture has received backing from firms including Blackstone, Hellman & Friedman, and Goldman Sachs. According to The Wall Street Journal, the venture has approximately $1.5 billion in committed capital. Meanwhile, OpenAI has received $4 billion from investors including TPG, Brookfield Asset Management, and Bain Capital, according to Bloomberg.
That roster of private equity firms gives the ventures a captive pipeline into a large base of portfolio companies. It’s not a consulting model in the traditional sense. Applied AI engineers from Anthropic will work alongside client organisations’ engineering teams, IT staff, and operations managers to redesign workflows from the ground up around Claude.
Both ventures are built on the same foundational logic. The bottleneck to enterprise AI adoption is not the technology itself, but the gap between a working demo and a production-grade system inside a regulated industry. Closing that gap requires engineers, domain expertise, and trust. Private equity firms, with their corporate networks and incentives, offer all three in exchange for a share of the upside.
“Enterprise demand for Claude is significantly outpacing any single delivery model. Our partnerships with the world's leading systems integrators are central to how Claude reaches large enterprises,” Krishna Rao, Chief Financial Officer of Anthropic, said in a statement. “This new firm brings additional operating capability to the ecosystem and capital from leading alternative asset managers.”
Srikanth Velamakanni, Co-founder and Group CEO of listed pure-play AI firm Fractal Analytics, believes that foundational models alone are not sufficient for enterprise deployment.
“Dedicated AI services are actively required to handle enterprise data, system, and business complexity; to drive accuracy within the context of enterprise data; and to drive change in large organisations,” he wrote on LinkedIn.
Velamakanni identified a demand-supply gap as the structural force behind both ventures. Enterprise appetite for AI transformation has grown sharply as AI has moved beyond knowledge retrieval into reasoning and agentic capabilities. But the capacity to actually deploy those systems inside large organisations has not kept pace. The ventures are, in his reading, attempting to close that gap at scale.
The Partnership Game
The Infosys-Anthropic partnership, announced at India's AI Impact Summit in February, integrates Claude models, including Claude Code, directly into Infosys Topaz, the company's AI platform.
HCLTech has its own agreement with OpenAI. Wipro has aligned with Microsoft. Cognizant and Accenture are running their own GenAI practices at scale.
This points to structural interdependence. “AI companies need services companies, and services companies in turn need native AI companies. They cannot work in a disconnected manner. Both have to come together to design what we would call the next-generation enterprise AI stack for the customer,” notes Vasu.
If those deployments deliver measurable returns on compliance costs, engineering productivity, and customer service operations, the market may respond positively. If they struggle, as many AI pilots have, the narrative will shift.
The deepest uncertainty is about how the enterprise software stack of the next decade will be assembled, and who will control each layer.
For decades, the architecture was stable. Companies bought systems of record—SAP, Salesforce, ServiceNow, Workday—and hired IT services firms to implement and maintain them. Hyperscalers such as AWS, Azure, and Google Cloud provided infrastructure, while consulting firms like Accenture and Deloitte advised on strategy.
AI firms are now reshaping every layer simultaneously.