After years of experimentation, India’s biggest software exporters say the waiting game is over. Consequently, many early AI pilots are morphing into large revenue contracts. Indian IT vendors now compete aggressively to monetise production-grade artificial intelligence. Moreover, executives highlight surging run-rates, swelling pipelines, and larger deal terms. This article analyses the data, the opportunities, and the unresolved challenges shaping the next chapter for Indian IT.

Across recent Q3 FY26 earnings, Tata Consultancy Services, Infosys, and HCLTech reported strong AI traction. TCS alone disclosed an annualised $1.8 billion from AI work. Infosys claimed 4,600 active projects and 500 deployed agents. Meanwhile, sector analysts estimate that roughly 74 percent of new contracts signed since mid-2024 revolve around artificial intelligence. Nevertheless, Forrester warns only 10-15 percent of experiments reach full production. Therefore, decision-makers must separate hype from durable value. The following sections explore how small proofs become scaled contracts, which metrics matter, and why skill development remains critical.

Market Momentum Rapidly Surges

Investor sentiment rebounded sharply during the December quarter. Moreover, each leading firm posted double-digit sequential growth on its declared AI revenue line. TCS reported 17.3 percent quarter-on-quarter growth, while HCLTech recorded about 20 percent. In contrast, overall sector revenue grew in low single digits. Industry observers view the divergence as evidence that AI pilots are now scaling.

For Indian IT executives, 2025 became an inflection point. Subsequently, boards approved bigger budgets that embedded AI into core modernisation programs. Infosys CEO Salil Parekh said 90 percent of the company’s top 200 clients now run AI initiatives. Additionally, HCLTech disclosed bookings of $3 billion, most of which include advanced AI deliverables.

Momentum is real, supported by disclosed numbers. However, headline growth still masks wide performance gaps across clients. Therefore, understanding new revenue reporting practices becomes essential.

Revenue Metrics Go Public

Until recently, Indian IT providers bundled AI work inside broader digital categories. Consequently, investors struggled to track progress. That changed in 2025 when multiple Indian IT majors introduced dedicated AI revenue lines. TCS now publishes an annualised figure, currently $1.8 billion. HCLTech labels its stream “Advanced AI”, reporting roughly $146 million for Q3.

Furthermore, Infosys highlights total contract value rather than pure revenue. The firm booked $4.8 billion in large deals last quarter, with AI dominating the mix. Meanwhile, HDFC Securities says 74 percent of recent contracts across the cohort were AI-centric.

• TCS: $1.8 billion annualised AI services; $9.3 billion Q3 TCV
• Infosys: 4,600 AI projects; 500 AI agents; $4.8 billion large-deal TCV
• HCLTech: $3 billion bookings; $146 million Advanced AI revenue
• Sector revenue: estimated $283 billion FY25 overall market size

Transparency bolsters credibility and attracts capital. Nevertheless, divergent definitions of “AI revenue” complicate comparisons. Next, we examine how Enterprise deals themselves are changing.

Enterprise Deals Rapidly Evolve

Clients no longer sign narrow proofs-of-concept. Instead, they bundle cloud modernisation, data engineering, and AI pilots into single, multi-year contracts. Consequently, contract values climb. One example is HCLTech’s $473 million five-year engagement with a global apparel retailer. Indian IT negotiators now pair AI commitments with legacy refresh cycles.

Enterprise deals now often include clauses that tie payments to efficiency gains delivered by AI agents. Moreover, longer sales cycles reflect heightened governance scrutiny. LTIMindtree noted that senior risk committees review model explainability before green-lighting spending. Nevertheless, once approved, agreements lock in three-to-five-year roadmaps, giving vendors predictable revenue.

The deal structure thus shifts risk while deepening vendor entrenchment. However, scaling those commitments remains difficult, as the next section discusses.

Scaling Efforts Remain Elusive

Forrester estimates that only 10-15 percent of AI pilots achieve sustained production. In contrast, vendor statements often cite thousands of deployments. Therefore, numbers can mislead if pilots and production are conflated. Data quality, workflow redesign, and governance emerge as common bottlenecks.

Additionally, measurement of business value lags technology rollout. Gartner surveys find many live systems lack clear P&L impact. Consequently, CFOs demand tighter ROI models before funding fresh initiatives.

Several Indian IT clients struggle with data readiness. Without disciplined operating models, early projects risk drifting into pilot purgatory, burning time and goodwill.

The scale gap tests vendor credibility and client patience. Nevertheless, deeper partnerships with hyperscalers may accelerate resolution.

Partner Ecosystem Quickly Expands

Global partners view Indian IT as an essential channel. Indian IT firms team up with AWS, Microsoft, Google Cloud, and Nvidia to speed deployments. Moreover, joint solution accelerators shorten proof phases and reduce integration work. Infosys, for instance, integrated its Topaz platform with AWS services in January 2026.

Consequently, larger contracts often include cloud capacity commitments alongside AI services. These bundled offerings appeal to procurement heads seeking one-stop solutions. Furthermore, hyperscalers gain access to regulated industries through local service partners.

Ecosystem alignment lowers technical friction and strengthens go-to-market reach. However, talent remains the decisive differentiator, which the following section explores.

Workforce Upskilling Sharp Focus

Vendors launched massive training programs to build prompt engineering, agent development, and governance skills. TCS alone reskilled over 300,000 employees on generative AI concepts during 2025. Additionally, companies market new certification pathways to clients.

Professionals can enhance their expertise with the AI Writer™ Certification, which validates applied AI content skills.

Moreover, reskilling mitigates workforce disruption as automation accelerates. Nevertheless, visa policy changes and rising labour costs pose headwinds that could offset productivity gains.

Teams trained on earlier proofs now serve as internal champions, hastening adoption across portfolios.

Human capital investment underpins sustainable differentiation. Consequently, the industry outlook depends on talent depth as much as technology.

Strategic Outlook For 2026

Analysts predict continued momentum, yet volatility will persist. HDFC Securities expects AI-led contracts to drive a sector recovery in 2026. Nevertheless, Forrester advises that real value hinges on closing the scale gap.

Boards plan higher R&D allocations, expanded partner programs, and refined metrics. Furthermore, progressive clients will demand outcome guarantees in Enterprise deals, enforcing discipline. Therefore, vendors that translate AI pilots into measurable savings stand to win disproportionate share.

For Indian IT leaders, the imperative is clear: convert innovation buzz into durable, margin-accretive revenue.

The coming year will test strategies, metrics, and talent pipelines. However, evidence suggests the transition from experiment to scale is firmly underway.

In summary, Indian IT has entered a pivotal phase where AI pilots morph into sizeable Enterprise deals. Data from TCS, Infosys, and HCLTech show revenue traction, while analyst research highlights both momentum and scaling obstacles. Furthermore, evolving contract structures, robust partner networks, and aggressive upskilling point to sustained growth. Nevertheless, only disciplined governance will turn technical deployments into financial outcomes. Professionals should continually upgrade skills to stay relevant. Consequently, exploring credentials such as the AI Writer™ Certification can sharpen competitive advantage. Act now to harness the full potential of enterprise artificial intelligence.