India’s technology services industry is staring at what its apex trade body calls a once-in-a-generation opportunity. Nasscom projects that agentic AI, systems capable of independently planning and executing multi-step tasks rather than simply answering prompts, could add $300 to $400 billion in addressable technology services spending globally by 2030. Indian firms already earn an estimated $10 to $12 billion annually from AI-related services, positioning the country’s outsourcing giants to capture a disproportionate share of that expanding pie if they can move quickly enough.
From Chatbots to Autonomous Workflows
The shift Nasscom is describing is qualitative as much as quantitative. Early generative AI adoption in enterprises centred on chatbots and copilots that assist a human user. Agentic AI systems go further, chaining together reasoning, tool use and decision-making to complete entire workflows, such as reconciling financial records, triaging customer support tickets end-to-end, or managing parts of a software development pipeline with minimal human intervention. For India’s services companies, whose core business has long been executing exactly this kind of repetitive, process-heavy work for global clients, agentic AI represents both an existential threat to old delivery models and a lucrative new service line to sell.
India’s Talent Constraint
The opportunity comes with a significant bottleneck. India counts more than 2 million AI-skilled professionals, yet only 100,000 to 200,000 of them have advanced skills capable of designing and deploying production-grade agentic systems. That gap between broad AI familiarity and deep, deployable expertise is why enterprises and services firms alike report difficulty hiring people who can actually ship working agentic AI products rather than prototype demonstrations. Closing this gap is likely to determine how much of the projected $300-400 billion opportunity Indian firms actually capture versus ceding to competitors in the United States, China or Europe.
Strategic Dependence on Frontier Models
Underlying the opportunity is an uncomfortable strategic reality: India does not currently possess frontier-level foundation models of its own comparable to those built by the largest US and Chinese AI labs. Policy commentary circulating alongside Nasscom’s projections argues that India cannot realistically outspend global frontier AI investment, and so must instead focus on deepening backward linkages, closely integrating with frontier model providers, while building forward linkages that let Indian firms create differentiated products and services layered on top of those models rather than competing to build foundation models from scratch.
A Complicating Geopolitical Backdrop
That dependence has already produced friction. The reported US government direction for Anthropic to suspend foreign national access to certain frontier models on national security grounds illustrates how exposed India’s AI services ambitions are to decisions made well outside its borders. For an industry planning to build hundreds of billions of dollars in new services on top of foreign frontier models, such restrictions are a reminder that geopolitical risk now sits alongside talent and technology as a core planning variable.
Industry Response and Outlook
Domestically, the response has included efforts like the AI-powered Bhashini language platform, which has crossed 1.2 million downloads and supports translation and speech services across 36-plus Indian languages, part of a wider push to build sovereign AI capability even while services firms lean on global frontier models for enterprise delivery. Nasscom’s framing suggests the next few years will be less about whether India can benefit from agentic AI and more about how fast the country’s talent pipeline and policy environment can adapt to capture a leading share of a market that is expanding faster than almost any other segment of enterprise technology spending.
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