Indian IT firms gain strategic importance for global AI labs as enterprises prioritise AI deployment, integration, governance and measurable business outcomes

Indian IT services companies are emerging as indispensable partners for leading global artificial intelligence labs as enterprises shift focus from model capability to deployment, integration and change management, a new report has said.
The Indian IT industry has traditionally owned these areas which help move pilots into production and such skills are in the spotlight of firms such as OpenAI and Anthropic, the report from brokerage UBS said. OpenAI has flagged that demand for enterprise deployment of its coding assistant Codex outpaced its own capacity to help clients adopt it, prompting partnerships with global systems integrators (GSIs) including Accenture, Capgemini, Cognizant, Infosys and Tata Consultancy Services.

Anthropic also acknowledged that a successful pilot is different from a running system a business can actually depend upon, adding that companies that succeed with AI integration typically do so with partners who have executed such projects before. Infosys features on both frontier labs' partner roster and TCS is mentioned specifically among Anthropic's partners.
The brokerage noted that firms feel that unclear return on investment, data readiness and governance are the major barriers to scaling AI deployments, rather than model performance itself. Management commentary across nearly all major Indian IT companies during Q1 FY27 earnings season showed that clients demanded measurable outcomes, governance frameworks and stronger data foundations before committing to large-scale AI rollouts. Infosys management mentioned that clients have increased allocation toward AI, infrastructure, data readiness and cloud platforms, indicating that data preparedness, not model access, is now the gating factor for AI implementation.
TCS also felt AI governance ranking among top priorities of enterprises, with clients demanding end-to-end accountability on return on investment even as their existing technology stacks often lack readiness for AI scaling.
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