India’s tech industry set to hit $315 billion in FY26 as AI drives growth: NASSCOM

India’s technology industry is projected to reach $315 billion in revenue in FY26, growing 6.1% year-on-year from $297 billion in FY25, according to NASSCOM’s Annual Strategic Review 2026.

In a year marked by global economic uncertainty and regulatory fragmentation, technology demand remained resilient. However, spending priorities changed. Enterprises moved decisively toward measurable return on investment, productivity gains and outcome-led transformation.

Exports are expected to exceed $246 billion in FY26, up 5.6% year-on-year. Domestic demand expanded 7.9%, reflecting steady enterprise technology adoption in India even as global macro pressures weighed on traditional markets. Growth in APAC and the Middle East outpaced mature geographies, helping firms diversify revenue streams.

AI has emerged as a meaningful revenue contributor. NASSCOM estimates AI revenues at $10–12 billion in FY26. On average, 5–6% of company revenues are now AI-led. The shift reflects a move from fragmented pilots to scaled, domain-centric deployments aligned with business outcomes.

The industry added approximately 135,000 employees in FY26, taking total direct headcount to around 6 million, a 2.3% increase over last year. Despite automation concerns, the sector remains a net hirer. More than 2 million professionals were upskilled in AI during the year, including 200,000 to 300,000 in advanced AI capabilities.

Sindhu Gangadharan, Chairperson, NASSCOM, said, “AI is accelerating productivity and changing the nature of work, but it is also expanding the opportunity frontier. As AI gets embedded across functions, we will see roles redesigned around outcomes, deeper specialisation, and significantly higher AI fluency. The industry’s focus is on building ‘Human + AI’ teams, investing in continuous skilling, and converting efficiency gains into growth, creating new jobs and new career pathways even as delivery becomes more agile and more resilient.”

The report describes the year as a decisive inflection point, with AI moving from experimentation to function-specific integration. “Human + AI” teams are emerging as the dominant delivery construct. Talent strategies are shifting from headcount-led hiring to capability-first models as AI-driven productivity improves. New roles such as AI orchestrators and human-AI managers are expected to expand faster than the broader digital workforce.

Growth continues to be led by ER&D and BPM. Engineering Research and Development is emerging as the fastest-growing pillar, with a shift toward IP-led lifecycle ownership. Providers are embedding intelligence directly into products and systems, moving from point engagements to end-to-end mandates. BPM firms are combining AI and data to move beyond robotic process automation, from automating tasks to enabling decision-making.

Global Capability Centres remain central to India’s tech momentum. Nearly 70% of GCCs have defined an AI roadmap. Many are transitioning from scale-focused execution to strategic ownership across critical functions. The model is evolving toward GCC-as-a-service, with deeper integration across cybersecurity, data analytics and cloud.

Rajesh Nambiar, President, NASSCOM, said, “The past year has been a reset for the global environment, but technology demand has remained resilient; shifting decisively toward productivity, measurable ROI and scaled AI deployments. India’s AI advantage is widening, making organisations more agile and outcome led. At the same time, growth engines like GCCs and ER&D are moving up the value chain, from scale to strategic ownership, reinforcing India’s role as a trusted partner built on cyber resilience and responsible AI.”

The findings are reinforced by the NASSCOM Global End User CXO Survey. Among global technology buyers, 86% expect business demand to remain stable or increase in CY26, including 56% who anticipate growth over CY25. About 90% indicate increasing AI allocation within digital budgets in CY26, signalling that AI is moving from discretionary experimentation to scaled, budget-backed deployment.