In many office parks across Bengaluru, Pune and Hyderabad, large teams once handled the routine work of global companies. They answered customer calls, monitored telecom networks and processed insurance forms. India’s technology services industry was built on that model: skilled workers delivering back-office support at scale for clients in the United States, Europe and Asia. That model is now being adjusted as India’s tech leaders roll out Nvidia AI agents at scale.
Major Indian IT firms including Infosys, Wipro and Tech Mahindra are deploying enterprise AI agents powered by software from NVIDIA. The tools are built on NVIDIA’s Nemotron models and AI Enterprise platform, and they are being integrated directly into business operations across call centres, telecom networks, healthcare administration and software development.
The shift is about internal systems that can complete tasks with limited supervision. These AI agents can review service tickets, search through large datasets, generate code, assist customer service representatives and support compliance processes in regulated industries.
For India’s IT services sector, which generates hundreds of billions of dollars in annual revenue, the economic implications are significant. The industry has long grown by hiring more people and expanding delivery centres. AI agents introduce a different equation. Instead of increasing headcount to grow revenue, firms are trying to increase productivity per employee.
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In call centres, AI systems can now handle routine queries while human staff focus on complex cases. This reduces training cycles and allows companies to manage peak demand without hiring thousands of temporary workers. In telecom operations, AI models help prioritise network repairs and improve the quality of technical recommendations. Even small efficiency gains can lower operational costs in a sector where margins are tight and infrastructure is expensive.
Software development is also being reshaped. Infosys has built smaller language models designed to assist with coding tasks inside secure enterprise environments. These systems can run on company data centres or private clouds, which is important for clients in industries with strict data rules. Rather than sending sensitive data to public AI platforms, companies can deploy AI tools within their own controlled infrastructure.
The changes reflect a broader shift in incentives. Global clients are under pressure to cut costs while improving service speed and reliability. AI agents promise faster turnaround times and fewer manual errors. For Indian service providers, offering AI-enabled operations helps defend contracts and maintain relevance as automation becomes central to corporate strategy. But the transition comes with constraints.
First, AI deployment is capital-intensive. It requires advanced chips, reliable data centres and stable electricity supply. India has made progress in digital infrastructure, but scaling AI workloads nationwide will require sustained investment. Firms must also manage cybersecurity risks and ensure AI systems operate within regulatory frameworks, especially in healthcare and financial services.
Second, there is the workforce question. India’s IT industry employs millions of people, many in roles that AI agents can partially automate. Companies say they are reskilling staff for higher-value tasks such as AI oversight, system design and data governance. The speed of that retraining will shape how smoothly the industry adapts.
Third, clients must see measurable returns. Large AI deployments involve upfront costs before efficiency gains are realised. In a cautious economic environment, enterprises want clear evidence that automation will improve margins without introducing operational risk.
What is emerging is not the end of India’s services model, but its evolution. Instead of relying primarily on labour scale, firms are combining human expertise with AI infrastructure. The goal is to move up the value chain from processing tasks to managing intelligent systems that run those tasks.
If executed carefully, this shift could strengthen India’s position in global technology supply chains. It would allow local firms to capture more value through proprietary tools and integrated platforms rather than time-based billing alone.
The outcome, however, will depend on execution. AI agents must prove reliable in real business settings. Infrastructure must keep pace with demand. And the industry must balance automation with employment stability.
India’s IT sector was built on disciplined delivery and cost efficiency. Its next phase will depend on how well it manages capital, compute and people in an AI-driven economy.
