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The AI boom is reshaping India’s IT industry, bringing new growth opportunities and fresh challenges for traditional service models. (Img: X)
Bengaluru: Artificial intelligence is emerging as a major growth opportunity for India’s IT services industry, as companies move from pilot projects and proof-of-concept deployments towards enterprise-wide implementation, AI-led consulting and measurable business outcomes.
According to the figures provided for the September quarter of FY2026-27, Tata Consultancy Services (TCS), Infosys, HCLTech and LTIMindtree together generated approximately USD 1.7 billion, or around Rs 16,169 crore, in AI-related revenue. The figures underline the growing commercial significance of AI for India’s technology services sector, even as companies face pressure to demonstrate returns on client investments and defend the pricing of traditional IT services.
TCS leads the reported quarterly comparison with USD 775 million in AI-related revenue, followed by Infosys at USD 540 million. HCLTech reported USD 219 million, while LTIMindtree recorded USD 166 million, according to the supplied figures. However, the companies use different definitions and reporting approaches for AI-related business, so these numbers should not automatically be interpreted as a like-for-like ranking of their AI operations.
TCS separately reported annualised AI revenue of USD 3.1 billion for Q2 FY2026-27, equivalent to more than 10% of its overall revenue. Infosys reported AI revenue of USD 540 million for the quarter, while HCLTech disclosed USD 219 million in advanced AI revenue
The growing contribution of AI is changing how Indian IT companies position themselves in the global technology market. Traditionally dependent on application development, software maintenance, infrastructure management and large outsourcing contracts, the industry is increasingly pitching AI-enabled transformation, automation and intelligent enterprise platforms as higher-value services.
TCS has emerged as a prominent player in this transition. Its management has emphasised helping customers convert advances in AI into measurable business outcomes, including improved productivity, more efficient business processes and better service delivery. The company’s AI strategy increasingly centres on integrating AI capabilities into enterprise systems rather than treating them as standalone technology deployments.
The opportunity extends beyond generating revenue from AI tools themselves. Large businesses need support with data infrastructure, legacy-system modernisation, cloud migration, cybersecurity, workflow redesign and the integration of AI into existing operations.
These requirements can create additional consulting and implementation opportunities for IT services providers. For companies such as TCS, the commercial challenge is to turn experimental AI projects into sustained engagements that generate recurring revenue and deliver demonstrable value to clients.
Infosys is also expanding its AI-led transformation business, with cost optimisation, vendor consolidation, core-system modernisation and enterprise-wide AI adoption remaining important priorities.
The company’s management has indicated that competitive intensity remains high, making differentiated solutions, stronger sales capabilities and deeper industry expertise increasingly important for converting opportunities into contracts.
At the same time, AI is creating a structural challenge for conventional IT services pricing. Infosys has acknowledged that AI-driven productivity gains are also compressing pricing in traditional services.
This creates a complex commercial equation for technology providers. If AI enables software development, testing, maintenance and other tasks to be completed more quickly, clients may expect lower costs or shorter project timelines. Service providers must therefore find ways to monetise higher-value AI capabilities while managing the potential erosion of revenue from labour-intensive engagements.
The long-term winners may be companies that can combine AI expertise with domain knowledge, enterprise integration capabilities and clear evidence of business value. Simply deploying AI tools may not be enough to sustain premium pricing if customers cannot see measurable improvements in efficiency, quality or revenue.
HCLTech has highlighted AI as an increasingly important enabler of productivity improvements, service quality and stronger client outcomes. Its strategy includes deepening existing customer relationships and expanding the scale of engagements through AI-led transformation programmes.
The company has reported USD 219 million in advanced AI revenue for the September quarter, with management indicating that AI-led transformation is becoming an important component of major client wins.
For HCLTech, the opportunity lies in embedding AI into broader technology and business transformation projects. These engagements can involve modernising legacy applications, automating workflows, improving software engineering productivity and integrating AI capabilities into enterprise platforms.
Larger transformation contracts can also create opportunities for long-term client partnerships. However, their commercial success will depend on implementation quality, measurable productivity gains, the ability to scale solutions across business functions and the customer’s willingness to invest in further transformation.
LTIMindtree is also benefiting from the growing demand for AI-related services. The supplied figures place its AI revenue at USD 166 million for the September quarter, with AI accounting for more than 10% of its quarterly revenue.
For mid-to-large technology services providers, AI adoption creates opportunities to compete through specialised industry solutions, consulting expertise and the integration of advanced technology into existing business processes.
The broader market is moving towards enterprise AI deployments that can support functions such as customer service, financial operations, software development, supply-chain management and business analytics. This expands the potential market beyond organisations experimenting with standalone generative AI applications.
However, the ability to convert demand into sustainable revenue will depend on execution, customer adoption, the availability of reliable enterprise data and the commercial viability of individual projects.
Wipro did not disclose a directly comparable AI revenue figure in the information provided. The company nevertheless indicated that clients continue to prioritise operational efficiency and productivity while looking to accelerate AI adoption and generate long-term business value.
This reflects a broader trend across the IT services industry: customers increasingly expect technology investments to deliver practical results rather than remain limited to experimentation or pilot programmes.
AI-related engagements can help businesses automate repetitive processes, improve decision-making, streamline operations and modernise technology infrastructure. For service providers, the challenge is to demonstrate that these benefits justify the cost of implementation and ongoing support.
The absence of a comparable revenue figure also highlights a limitation in measuring the industry’s AI performance. Companies may classify AI revenue, advanced AI services, AI-enabled transformation and annualised AI business differently, making direct comparisons difficult without consistent reporting standards.
The growing commercialisation of artificial intelligence comes at a critical time for India’s IT services sector, which is navigating cautious client spending, competitive pressure and changes in the economics of software delivery.
The latest figures suggest that AI is becoming a meaningful contributor to the revenue mix of leading companies. Yet revenue growth alone does not establish how profitable these services are, how much traditional business they may replace or how quickly clients are moving from pilot projects to large-scale deployments.
The industry is also confronting a broader shift in its traditional business model. For decades, many IT services contracts were structured around project teams, employee hours and long-term outsourcing arrangements. AI-powered automation could reduce the human effort required for some of these tasks, potentially changing how contracts are priced and how service providers recognise value.
At the same time, AI adoption creates demand for new capabilities in data engineering, model integration, governance, cybersecurity, cloud infrastructure and enterprise transformation. These areas could provide additional growth opportunities for firms that can combine technical expertise with deep knowledge of client industries.
The competitive advantage is therefore likely to depend on more than AI revenue figures. Companies will need to show that they can scale deployments responsibly, protect sensitive data, manage implementation risks and deliver outcomes that clients can measure.
The next phase of the AI race will be shaped by how effectively Indian IT companies convert customer interest into large, repeatable commercial engagements. Investors and industry observers will be watching revenue disclosures, deal wins, AI adoption rates, productivity improvements and the effect of automation on traditional services.
TCS will be under pressure to build on its reported annualised AI revenue momentum. Infosys will need to balance AI-led growth with pricing pressure in conventional services. HCLTech will look to deepen AI-driven client relationships, while LTIMindtree will need to demonstrate that its expanding AI business can sustain growth and create measurable value. Wipro’s future disclosures will also be important in assessing its performance against competitors.
For customers, the priority will be obtaining reliable returns on AI investments. For technology workers, the transition could change job roles, required skills and the composition of project teams, increasing the importance of reskilling and specialised expertise.
Ultimately, AI is becoming both a revenue opportunity and a source of disruption for India’s IT services industry. The companies best positioned to benefit will be those that turn technological advances into commercially sustainable solutions without allowing automation-driven efficiencies to undermine the value of their traditional businesses.
