For India's IT giants TCS and Infosys, AI both dents and supports growth

Artificial intelligence is technology that performs tasks requiring human-like abilities, such as analyzing information, finding patterns, or generating outputs. In this article, AI matters because it is changing how major IT companies earn money. It creates new, high-margin work while also reducing some traditional demand.

TCS is using AI through deployment across legacy software systems, meaning older client technologies are being upgraded or connected with AI capabilities. Infosys is likewise benefiting from AI-related business, although the article does not describe specific products or projects. Their reported AI revenue shows that clients are paying for this transition.

The results are mixed. TCS’s annualized AI revenue grew more than 19% in the July–September quarter. Infosys’s AI revenue rose 29% quarter-on-quarter. Yet AI productivity gains can make traditional services require fewer hours, squeezing overall revenue. The companies therefore face both opportunity and disruption as AI adoption spreads.

TCS and Infosys both reported strong AI-related revenue growth in the July–September quarter. TCS’s annualized artificial-intelligence revenue grew more than 19%. Infosys’s AI revenue rose 29% quarter-on-quarter. These figures measure growth differently, so they should not be treated as a direct like-for-like comparison.

The difference matters. TCS’s figure describes an annualized revenue measure, while Infosys’s figure compares one quarter with the previous quarter. Even so, both point to increasing income connected with AI. The article links this growth to the wider deployment of AI across legacy software systems and related business services.

The gains do not mean the companies’ total businesses are expanding equally quickly. AI is also producing productivity improvements that can reduce traditional service work. As a result, AI revenue is rising while overall revenues remain under pressure. The quarter therefore highlights both the promise and the disruption created by AI adoption.

The central tension is simple: AI creates new work while reducing the amount of some older work. TCS and Infosys can earn from helping clients deploy AI, but clients may also use AI to complete software and business tasks more efficiently. That can weaken demand for traditional services and put total revenue under pressure.

The article gives both sides of the picture. TCS’s annualized AI revenue grew more than 19% in July–September. Infosys’s AI revenue rose 29% from the previous quarter. At the same time, analysts cited AI-led productivity gains as a force squeezing revenues in traditional segments. New AI income therefore does not automatically replace every lost dollar.

This creates a difficult transition. The companies must win AI-related contracts while adapting to a business model that may need fewer human hours for certain tasks. Their recent earnings offer hope, but also caution. Growth will depend on whether new, high-margin AI work offsets shrinking traditional demand.

Legacy software systems are older technologies that businesses still depend on. Deploying AI across them is not simply a matter of switching on a new tool. It can involve adapting existing systems, connecting new AI capabilities, and making the combined setup work reliably. That complexity creates demand for specialist IT services.

The article says deployment across legacy software systems is driving growth in high-margin contracts for TCS and Infosys. Their teams can help clients move from older technology toward AI-enabled operations. This work may include planning, integration, technical changes, and continuing support, although the article does not list specific projects. The key mechanism is the difficult bridge between existing systems and new AI.

Such contracts can be valuable because clients need tailored work rather than a simple, standard purchase. They may also require ongoing expertise as systems change. However, the article presents this opportunity alongside a warning: the same AI adoption can improve productivity and reduce traditional service demand. Integration growth and efficiency pressure are happening together.

AI productivity gains mean workers or systems can complete certain tasks more quickly or with less effort. In traditional IT services, revenue can be linked to the people and hours needed for software development, maintenance, testing, or support. If AI reduces that workload, clients may need fewer service hours from providers such as TCS and Infosys.

The article describes this effect directly. AI-led productivity gains are squeezing revenues in traditional segments, even while AI-related income increases. For example, a client might use AI-enabled tools to speed routine software work. The article does not specify a particular task, but its broader point is that efficiency can reduce the amount of older service work purchased.

That creates a revenue challenge. New AI deployment contracts may carry high margins, but they must grow quickly enough to offset weaker traditional demand. TCS and Infosys therefore face a transition rather than a simple expansion. Their earnings show that AI supports growth in one area while putting pressure on another.

The article does not identify specific non-AI businesses that TCS and Infosys plan to expand. It only says that AI deployment across legacy systems is driving high-margin contracts, while AI productivity gains pressure traditional segments. Any additional areas therefore come from established knowledge about IT-services companies, not from this article.

Possible areas include technology consulting, cloud migration, cybersecurity, data management, business-process services, and long-term system operations. These services can help clients redesign technology, protect systems, manage information, or run applications. They may also connect naturally with AI deployment, especially when older systems need broader modernization. The source does not provide revenue figures or plans for these areas.

The broader lesson is diversification. If AI reduces routine software work, providers can seek services that require judgment, integration, security, or ongoing responsibility. They would still face pressure to improve productivity, though. The article’s evidence supports only the AI-related opportunity and the traditional-revenue squeeze, not a confirmed expansion strategy in these alternatives.

An IT-services company helps clients build, run, improve, or support technology systems. It may provide skilled employees, software expertise, system integration, maintenance, and business-process support. This definition uses general knowledge; the article itself only identifies TCS and Infosys as India’s top information technology companies and discusses their AI-related earnings.

Revenue can depend on the volume of human work and technology supplied. More projects, employees, service hours, software capabilities, or managed systems can create more billable activity. If AI makes a task faster, clients may need fewer hours, which can reduce traditional service revenue. If clients instead hire a provider to deploy AI across older systems, that creates new paid work.

This explains the mixed picture in the article. TCS and Infosys are gaining AI-related income, but AI-led productivity gains are squeezing traditional segments. Their business depends on balancing those forces. The companies can benefit when clients need complex technology changes, yet face pressure when automation reduces routine work.