Artificial ​intelligence promised to disrupt India’s IT industry and it is delivering.

Outsourcing giants like Tata Consultancy Services, Infosys, Wipro, HCLTech and Cognizant are rejigging business models, increasingly tying fees to performance outcomes ‌instead of hours worked, as clients demand steep price cuts and more productivity.

Industry executives also say they are losing some work entirely ​as customers use AI to shift tasks in-house, while all the uncertainty that the new technology has brought is resulting in shorter ⁠contracts.

And where once the big IT companies won contracts because they could point to their huge employee base, that has become less and less of an advantage as AI automates more and more tasks — levelling the playing field for smaller rivals which have jumped at opportunities to snatch business.

“It’s a desperate market for the service providers. The odds are very ‌much in favour of clients,” said Jimit Arora, CEO of research and advisory firm Everest Group.

Software companies globally have been battered by worries that AI will render key parts of their business obsolete, but India’s IT industry — worth $315 billion in annual revenue — is the most obvious victim ‌with its traditional reliance on billable hours.

The Nifty IT index has tumbled by a fifth this year, with its 10 constituents losing a combined $73 ‌billion ⁠in market value.

These days, pricing for contracts is more likely to be dictated by performance outcomes.

TCS Chief Executive K ⁠Krithivasan told Reuters that about 80% of the company’s contracts within its finance, human resources and other business services segment are now based on outcome performance measures.

That number represents a doubling since AI went mainstream in late 2023, said a person with knowledge of the matter, who was not authorised to speak to media and declined to be identified. TCS did not respond to a request ​for comment.

Other examples in the industry include an AI and ‌automation deal Cognizant struck with Daimler Truck in February. It stipulated AI-related cost savings would be split between the vendor and the client, according to people familiar with the terms.

“With AI, the fundamentals are shifting,” Cognizant said in a statement to Reuters, though it declined to comment on specific contracts. “Clients now expect more value and measurable outcomes, and we are re-forging our model for that reality.”

Daimler Truck did not respond to a request for comment.

A separate multiyear cloud ‌management deal forged in June 2025 was structured so HCLTech will not be paid by German utility E.ON for the first year, with payments ​from the second year tied to efficiency gains and specific business outcomes, according to two people familiar with the agreement.

E.ON declined to comment, while HCLTech did not respond to a request for comment.

As AI drives productivity gains, ⁠clients have become increasingly vocal about getting more for less.

Persistent Systems CEO Sandeep Kalra told Reuters that the IT provider’s clients were demanding the same work for 25% to 30% less while expecting faster delivery and higher productivity.

But on the plus side, AI is helping Persistent win larger deals than it would have previously.

“The demarcation of ‌a scale player only by revenue is not necessarily a big thing today,” he said.

IT executives and analysts alike say competition from mid-sized firms has become brutally fierce.

Many customers now want rapid development of pilot programmes and smaller firms are winning mandates by deploying senior leaders quickly and offering flexible pricing, says Phil Fersht, CEO and chief analyst at HFS Research.

“Many Tier 2 firms have been more agile and hungry in this phase,” he said.

Both Persistent and Coforge, another mid-sized IT services provider, have seen revenue in dollar terms grow by double digits for at least eight quarters in a row. In April-June, revenue for Persistent surged 16%, while Coforge’s sales jumped by a third.

In contrast, TCS, Infosys, Wipro and HCLTech had subdued growth of 1% to 3%.

As pressure from clients grows, some firms are ‌making rash decisions, says Tech Mahindra CEO Mohit Joshi.

Some rivals are factoring in productivity gains of 70% to 80% over five to seven years and guaranteeing prices despite rising chip costs, Joshi ​told an analysts’ call last month, adding that his company had chosen not to take such risks.

“Clearly, there is a ton of competition out there, and our competition at times is doing irrational things,” he said.

Infosys last month also told analysts it had ⁠walked away from contracts that were no longer economically viable.

TCS’s Krithivasan said that so far the company has been able to offset AI-related downward pressure on revenue with ⁠new work.

“But how fast and how much more we are able to go ahead of the (revenue) deflation will determine the growth going forward,” he added.

TCS is also boosting its numbers of engineers who embed with clients to accelerate AI adoption and is hunting for AI acquisitions.

It is thus ‌far the only Indian IT services provider to have announced mass layoffs in the AI era, implementing cuts of more than 12,000 last year. But companies have flagged that their traditional role as huge hirers of new recruits may be winding down.

The country’s IT giants will no longer need large ranks ​of entry-level engineers, according to former Infosys CFO V. Balakrishnan.

“The pyramid model is gone. With coding agents, we no longer need basic coding,” he said.

Published – August 21, 2026 09:27 am IST

“Nani, aaj kya banaya?” (”Grandma, what did you cook today?”)

It’s a simple question that millions of Indians ask every day. But what if you asked it to an AI assistant? Would it understand the language? The accent? The mix of Hindi and English? What if the question was asked in Tulu, Bundeli, Kodava or Santali instead?

Artificial intelligence has become more advanced at answering questions, translating languages and even writing stories. But there’s a catch. Most AI systems learnt these skills from enormous amounts of digital data — books, websites, videos and conversations, much of it in English. For many Indian languages and dialects, especially those spoken by smaller communities, that kind of digital treasure trove simply doesn’t exist.

So how do you teach a machine to understand a country where languages change every few hundred kilometres, accents shift from district to district, and some words are spoken every day but have never been written down?

That’s the challenge researchers at AI4Bharat, a research lab at IIT Madras, have taken on. Their mission is ambitious: to build AI that can understand, speak and translate India’s many languages, making technology more accessible to millions. We spoke to Kaushal Bhogale, a PhD researcher at AI4Bharat, to find out how his team is teaching AI to speak India, one voice, one conversation and one language at a time.

Why are Indian languages harder for AI?

When people think of artificial intelligence, they often assume it can understand every language equally well. In reality, AI is only as good as the information it learns from.

Languages like English have a huge advantage. The internet is filled with English books, websites, subtitles, podcasts, news articles and videos. This gives AI billions of examples to learn from.

Many Indian languages, however, don’t have the same amount of digital content. Researchers call them “low-resource languages” because there simply isn’t enough data available for AI to learn from. As Kaushal explains, “Many Indian languages are considered low-resource languages.”

The challenge doesn’t end there. India is one of the most linguistically diverse countries in the world. The way people speak can change from one district to the next. The same language may have different accents, dialects or local words. In some communities, certain words and expressions are spoken every day but have no standard written form.

For an AI model, this is like trying to learn cricket without ever watching a match. It needs thousands, often millions, of real examples before it can recognise patterns, understand meaning and respond accurately. That’s why collecting language data from across India is such an important part of AI4Bharat’s work. It isn’t just teaching AI new words; it’s helping machines understand the richness and diversity of how India speaks.

The great voice hunt

How do you teach an AI to understand the way people across India speak? You start by listening.

For AI4Bharat, that has meant travelling to more than 500 districts across the country to collect speech data from people of different ages, regions and language backgrounds. But this isn’t as simple as carrying a microphone and pressing record.

The team first connects with local colleges and community organisations before setting up recording booths where volunteers can participate. Instead of asking them to read random sentences, researchers encourage them to talk about their lives. Participants might describe how their family celebrates Diwali, explain the dishes prepared during festivals, talk about wedding traditions, or share stories about their village and community.

These conversations do much more than teach AI new words. They capture accents, dialects, expressions and cultural traditions that make every language unique. “People are happy to share their life experiences,” says Kaushal. What the team expected to be one of the biggest challenges, getting people to speak freely, turned out to be one of the most rewarding parts of the project.

Behind the scenes, every recording goes through another important step. Human transcribers carefully listen to the audio and write down exactly what was said. These speech-and-text pairs become the training material for AI models, helping them learn how spoken words match written language.

In many ways, AI4Bharat isn’t just collecting voices. It is creating a living archive of how India speaks—one conversation at a time.

So…how does AI actually learn?

At first glance, it might seem almost magical that an AI can recognise speech or translate between languages. But the way it learns isn’t all that different from how humans do.

Think about a young child learning what a cat is. No one explains that a cat has whiskers, pointed ears or a long tail. Instead, the child sees hundreds of examples. Over time, their brain begins to notice patterns and can recognise a cat almost instantly.

AI learns in a similar way. Instead of looking at hundreds of examples, however, it studies thousands—or even millions. Researchers feed the system huge amounts of data, allowing it to discover patterns on its own.

For language AI, those examples come in the form of speech recordings paired with written transcripts. As the AI processes more and more of these speech-and-text pairs, it begins to connect sounds with words, words with meanings, and sentences with ideas. Eventually, it becomes good enough to transcribe spoken conversations, translate between languages or even respond to questions.

“Researchers found that as we keep showing the AI more examples, its ability to recognise patterns becomes better,” says Kaushal. “That’s why collecting data is so important.”

In other words, every conversation recorded by AI4Bharat becomes another lesson for the AI, helping it understand the many ways India speaks.

When AI discovered words that couldn’t be written

Collecting voices from across India revealed an unexpected challenge, not every spoken word has a standard written form.

After each recording, human transcribers write down exactly what they hear so the AI can learn to match speech with text. But many Indian communities use words and expressions that are spoken every day yet rarely written. Some dialects have no standard spelling, while others differ greatly from formal written language.

Instead of forcing these words into existing rules, the team developed new transcription guidelines to record them accurately. “The spoken language is very different from the written language,” explains Kaushal. “This is especially true for Indian languages because of their many accents and dialects.”

In the process, AI4Bharat isn’t just training AI, it is also helping document India’s rich linguistic heritage.

More than just translation

The work at AI4Bharat goes far beyond translating languages. Its tools can convert speech into text, read text aloud in natural-sounding voices, transliterate words between scripts, and power chatbots, educational apps and government services. The team is also developing technology that can read printed documents in different Indian scripts.

What makes this work especially valuable is that it is open source. AI4Bharat makes its models freely available for researchers and developers to build upon. Many of these tools are also available through Bhashini, the Government of India’s language technology platform, helping create digital services that work across India’s many languages.

Every voice matters

India is home to hundreds of languages and thousands of dialects, but much of the digital world still works best in English. If AI learns only from a few languages, millions of people risk being left behind.

AI4Bharat’s goal is to change that by making technology accessible in the languages people use every day. As Kaushal explains, the aim is to bring language technology for Indian languages closer to what already exists for English.

Every voice recorded today could help tomorrow’s AI understand another corner of India.

C.P. Gurnani, co-founder and Chief Executive Officer, AIonOS and Vikram Sinha, President Director and Chief Executive Officer Indosat Ooredoo Hutchison sign MoU at Aerocity, in New Delhi, on January 27, 2025
| Photo Credit: PTI

The rapid uptake of Deepseek, the Chinese-developed artificial intelligence (AI) foundational large language model (LLM), has put the AI race in context, with the foundational model developer’s app leading even on American app store fronts.

In India, Gurugram-based company AionOS announced on Monday (January 27, 2025) that it plans to work with Deepseek — both with the open source model available to the general public and with the firm itself in Guangzhou — to open an AI centre of excellence in Indonesia, in partnership with the telco Indosat.

ALSO READ: What is DeepSeek, and why is it disrupting the AI sector?

The AI race has matured to the point where industry observers have marvelled on Chinese advancements in the field even in the face of punishing sanctions restricting availability to the most powerful hardware, such as GPUs and processors, that cutting-edge AI relies on.

Deepseek is able to demonstrate responses and analytical prowess that the OpenAI-backed ChatGPT does, with what is likely inferior hardware and lower cost. (Deepseek still considers the lack of access to advanced chips a hindrance, the firm’s CEO reportedly told Chinese officials)

India’s position in this race has so far been as a player taking advantage of downstream efficiencies — as AI models become cheaper and more open-source models become available to researchers and businesses to customise, firms have been working to take advantage of those shifts, rather than make expensive upfront investments in creating a foundational model.

From the government side, the focus has been on making local language solutions for translations, like the BHASHINI initiative, which has emerged as a key priority for improving linguistic accessibility in dozens of languages.

“Ultimately, the cost of technology has to reduce, the cost of processing has to reduce, and the cost of deployment has to reduce,” C.P. Gurnani, AionOS’s CEO and founder, and a former CEO of Tech Mahindra, said in a briefing on Monday (January 27, 2025).

When Sam Altman visited India last year, Mr. Gurnani accepted a challenge from the OpenAI CEO to build a foundational model in India, a clip that had gone viral. While that has not yet happened in the Indian industry, Mr. Gurnani said that “there will always be new developments that will happen because it is a very fast evolving industry, [where there is] a new announcement every week.”

Indian firms have not yet loudly announced any work around Deepseek, which as an open source model can be built on top of; Mr. Gurnani, for instance, was clear that while his firm was working with the firm, the output of those efforts would be limited to Indonesia.

“Indonesia is a neutral country,” said Vikram Sinha, Indosat’s CEO. Mr. Sinha, an Indian executive who has led a tripartite merger for the Indonesian telco, is in New Delhi as a part of the business delegation accompanying president Prabowo Subianto.

Aravind Srinivas, the CEO of San Francisco-headquartered Perplexity AI, Inc., a leading generative AI firm, indicated that these cost considerations should not lead to an averseness to building a foundational model.

“India must show the world that it’s capable of ISRO-like feet for AI,” Mr. Srinivas said last week on X, formerly Twitter, referring to the Indian space programme’s recent high profile successes.

Mr. Srinivas warned against falling into the “trap” of avoiding building foundational models like Deepseek due to the high expenses.

Mr. Srinivas’s posts followed a statement in December by Infosys co-founder Nandan Nilekani, who said at an event that building foundational models was “not the best use of” financial resources.

But Mr. Nilekani’s point was not that the money was better used building on top of existing models, but that India should instead build the computing and physical infrastructure that AI runs on, as building a foundational model now may involve using existing computing resources abroad.