Indian IT firms may profit from AI growth via asset-light models

The infrastructure cost barrier

Building and operating the physical capacity required for artificial intelligence is becoming a massive financial undertaking. As enterprises demand more computing power, the companies providing that infrastructure face significant funding requirements and high financial risks. This capital-intensive nature is creating a divide between the people building the 'pipes' and those using the water.

The research report by Anand Rathi highlights how these rising infrastructure investments are creating a bottleneck for some players. Companies must commit to substantial future computing obligations just to keep up with demand. This concentration of risk in the infrastructure layer means that the cost of entry for building large-scale AI capacity is becoming prohibitively high for many.

A clear example of this scale is seen in the finances of Anthropic. During the first half of calendar year 2026, the company saw its revenue jump 14-fold to reach USD 16.3 billion, yet it also faces approximately USD 321 billion in leases that have not yet started. These figures underscore the sheer magnitude of the money needed to sustain AI growth.

The asset-light advantage

Indian information technology companies are positioned to navigate this landscape using a different strategy. Rather than building the massive data centers or buying the hardware, these firms can operate on an asset-light business model. This allows them to participate in the AI boom without bearing the same level of capital expenditure as infrastructure providers.

The report notes that Indian IT firms are supported by net-cash balance sheets and low capital expenditure intensity. Because they do not need to own the underlying computing capacity, they can focus on service delivery and software solutions. This structure allows for strong cash conversion, as they are not tied down by the heavy costs of maintaining physical assets.

By staying on the sidelines of the infrastructure build-out, these companies can remain agile. They can provide the necessary services to enterprises that want to adopt AI but do not want to manage the complex hardware requirements themselves. This creates a distinct opportunity to capture value from the deployment cycle without the associated financial risks.

The rise of systems integrators

A major opportunity is emerging for systems integrators, which are companies that help businesses plug AI models into their existing technology. These providers are essential for making AI useful in a corporate setting, as they handle the integration into specific applications and workflows. They act as the bridge between raw AI power and practical business utility.

The report suggests that these roles are becoming increasingly important as companies look for model-agnostic solutions. This means businesses want to be able to select and deploy different AI models across their operations without being locked into a single provider. Systems integrators provide the expertise to manage this variety and ensure the technology works with current systems.

Evidence of this trend can be seen in the spending patterns of major AI players. Anthropic's costs for sales, marketing, and partnerships grew by about 27 times over a year, reaching USD 3.2 billion in the first half of calendar year 2026. Much of this was driven by channel-partner fees, signaling a growing reliance on third-party service providers to reach and support enterprise customers.

Market risks and headwinds

While the outlook for Indian IT firms is positive, the report also identifies several significant risks that could impact profitability. One primary concern is AI-led pricing deflation, where the increasing availability of AI tools might drive down the prices companies are willing to pay for IT services. This could squeeze margins for service providers who are not efficient enough to adapt.

Another risk involves the high cost of computing itself. Because companies are spending so much on the infrastructure layer, there is a possibility that this could constrain their discretionary technology spending. If a business is spending its entire budget on the raw computing power needed for AI, it may have less money left over for the custom services and integrations that IT firms provide.

The report suggests that the pace of growth for the Indian IT sector will depend on several moving parts. Success will rely on the actual demand from enterprises, the ability of firms to deliver high-quality integration services, and the overall impact of changing spending patterns. The transition to an AI-driven economy is not guaranteed to be profitable for every player involved.