India must focus on sustainable AI solutions that deliver long-term value creation

After a lacklustre 2025, Indian IT industry is taking several strategic steps to stay ahead in the AI era. Many IT firms are acquiring companies with sound AI-platforms and solutions, while companies like TCS have entered the data centre space for cashing in the emerging demand.

In a conversation with the Bizz Buzz, Chairman of venture capital firm, Exfinity Ventures & Former CFO of Infosys, V Balakrishnan said that Indian IT firms have to build their consulting prowess as that will be critical for selling more AI-led solutions to clients. He said that though IT firms are taking several steps in the AI space, efficacy of these steps will be known when those translate into revenue and profitability.

According to the veteran IT sector leader, India doesn’t need to build its own LLM (Large Language Model) given the high cost and resource requirement but it should build India-specific solutions based on those LLMs. He said though there are startups building good AI platforms from India, but the numbers are very few. Indian startups need to come up with AI solutions that are sustainable and provide long lasting solutions, he added

The year 2025 ended on a muted note for the global IT services industry. Indian IT firms’ revenue growth remained at a low single digit level. How do you see 2026 as far as growth environment is concerned? How will AI shape the demand environment?

The environment is too unstable. Even if the US economy is growing and in last quarter, it was 4.3 per cent growth; the underlying growth is driven by AI investment. The broader economy is still struggling. So, the IT spending will be muted.

In addition, the AI uncertainty related to client adoption and reduction in prices is also there. In this perspective, the environment remained stable and if there is growth, that will be great achievement. So, a low single digit kind of revenue growth is expected in 2026.

Many Indian IT firms have been aggressive on the M&A space in recent quarters. Many are building AI capabilities at a faster pace. How do you see these moves? Are they doing enough?

IT firms are making several moves. Whether that translates into revenue growth or not, that time will tell. Because corporates are still struggling with adoption of AI. Internally, their data and structure are not tuned towards AI.

They are figuring out how to do it. It is an interesting situation where companies are making a lot of noise on AI but its translation into revenue and profit will take time. As far as some IT firms giving AI revenue separately and some not giving it; it is a similar situation some years back when companies used to give digital revenue.

Increasingly, some part of the project will be AI-related. But at the end of the day, if companies are earning more AI revenue, it should be reflected in the per capita revenue and margin through efficiency improvement.

There is no point of focusing on AI revenue separately. Focusing on per capita revenue and profitability will provide good indicators of productivity gains coming from AI adoption.

What kind of strategies Indian IT firms should adopt for increasing their AI revenue?

The first thing they need is good consulting centre. Because in the AI environment, consulting needs to lead the sales. In that way, either they have to acquire some good AI consulting companies or acquire some good AI solution companies so that they can embed those in their business environment and translate into revenue as customers.

They have to do more acquisitions. IT firms have to do more hiring in different (domains) and consulting spaces to be in the game.

What will happen to the employee structure? Will the employee pyramid change in the coming time? Can you provide some perspective into this matter?

Of course, the employee structure is going to change. They are not going to hire many freshers. And most of the lower end of the coding will get automated. The IT firms will also reduce the middle level of the employee pyramid.

And they have to increase the top. In the new scenario, the bottom will be thin, the middle will shrink and the top will heavy. It may not happen in next one year but this is the kind of change that is going to happen.

In that way, the business model will change. Is that the right understanding?

Winning large deals and cutting down costs have its own limitations. It is matter of time that companies, which are not taking strategic steps, will be forced to do that. Market will force them to do that.

Companies like TCS have taken several strategic moves like entering into data centre business. How do you see these pivots in the current AI era?

Today, what is the resource that is not available in optimum amount? One is data centre and the other one is power. When you look at AI, zillions and zillions of data have to be stored. Models have to get those data and bring in the insight from the data. So, the storage becomes very important.

World doesn’t have that kind of data centre capacity now. Again, data centre consumes a lot of power and water. These are also scarce resources. When AI really explodes and becomes mainstream in the next 2-3 years, all these concerns will be very high.

So, if you are a service provider and your client wants access to data centre, then you are in a good position if you are holding part of that resource. That provides a better lead in the market. That’s what TCS is trying to do. So, different models will evolve with time.

What is your opinion about the AI startup ecosystem in India as of now? Are Indian startup building sound solutions for the world?

India doesn’t have a good AI story. Because all the LLMs belong to the US or China. India has not built any big LLM and I don’t think, India should waste its resources in building one. What India should look at is using the LLMs to build use cases in India for India-specific problems.

India will slowly come up in the AI space but now, we don’t have the resources, capital and the manpower for building that. As far as startups in India is concerned, there are a few good AI startups but a lot of noise is there.

We have to look at AI solutions that are sustainable and create more value. Number of these companies in this category are very less.