IT reset: Will AI be the disruptor? 

A few months back, Infosys dropped out of India’s top 10 most valued firms after its market capitalisation fell below ₹ 4.9 lakh crore following a nearly 7 per cent share price crash. A brutal selloff, fuelled by weak FY27 growth guidance and AI-driven industry concerns, caused the firm to lose over ₹ 2 lakh crore in value this year. A few months before that, Tata Consultancy Services (TCS), one of India’s largest technology firms, had lost the crown of being the most valuable company after 14 years. Is something brewing in the Indian IT services segment, or is the fast advent of AI leading to disruption in the whole sector?

For decades, India’s IT leadership was built on the traditional models: the efficient delivery of high-quality human intelligence at scale. However, as the rapid evolution of AI begins to replace humans and starts disrupting how services are delivered, the Indian IT services industry will have to reinvent itself to stay relevant. Indian IT services companies are facing structural challenges as AI rapidly devalues their traditional labour‑centric business models. AI-driven automation is breaking the linear relationship between headcount and revenue, eroding labour arbitrage advantages, and compressing margins.

Experts rightly agree that Indian IT firms clearly face some sort of revenue-deflation risk as AI reduces billable effort, making traditional time-and-materials less applicable. Analysts say that Indian IT services companies must invest in new AI platforms, assets, accelerators, and reskill at scale to continue staying relevant to the clients.

“There will be a new stream of revenue classified as "AI revenue" which ultimately becomes the only way to earn revenue in the near future. This revenue will have different delivery, operations and margins characteristics. Providers will have to calibrate their business' transition to this new reality. AI is a major disruptor, but deal size also reflects core transformation cycles and macro uncertainty. Like with every new technology, AI will also require both clients and providers to tread cautiously in the beginning, leading to smaller deal sizes, but as the economic climate improves, these sizes will improve,” explained Ashutosh Sharma, VP and Research Director, Forrester.

Clients are shifting from effort-based contracts to outcome-driven, AI-enabled service models, reducing demand for large-scale manual delivery. At the same time, providers are forced to absorb high upfront investments in AI platforms, compute infrastructure, and large-scale reskilling while navigating increasing regulatory scrutiny, data governance requirements, and geopolitical constraints. These forces are making traditional ways of working outdated, so Indian IT companies are turning to new solutions, focusing on outcomes, and using AI to stay competitive.

“The advent of AI, particularly autonomous and agentic AI, has emerged as a major disruptor, fundamentally altering deal dynamics across the industry. AI-driven automation is compressing delivery costs and shifting the competitive advantage from labour arbitrage to technology arbitrage. As a result, providers are being forced to reassess their margin structures and growth strategies, while clients are increasingly benchmarking contract values against the automation potential of AI rather than traditional headcount metrics. This has led to immediate pricing pressure and a noticeable acceleration in contract renegotiations, especially within managed IT services,” Biswajit Maity, Senior Principal Analyst at Gartner, told THE WEEK.

He adds that client buying behaviour is evolving rapidly and organisations now favour short AI pilots, targeted use-case projects, and incremental enhancements instead of committing to large, long-term outsourcing deals. “This shift has resulted in smaller, more modular deal sizes and a move away from the legacy model of mega-deals. AI is undeniably the primary disruptor driving these changes, compelling Indian IT services companies to adapt their offerings and engagement models to remain competitive in an AI-first market,” added Maity.

The big shift is that AI can cut delivery time by 50 per cent or more in some services, but it doesn’t remove the surrounding engineering work (requirements, architecture, integration, testing, governance). For instance, AI will write code, but engineers will build everything around it. 

Still, on an overall basis, unit costs are falling, but volume and complexity are rising – this is driving a mix shift from commodity coding to integration, orchestration, and domain AI work. Pricing pressures are also truly showing up as clients demand discounts and transparency on AI productivity gains.

Is the traditional shaped pyramid workforce model giving shape to the diamond shaped model?

IT experts agree that as AI automates routine work, demand concentrates in mid-level specialists (architecture, domain, orchestration, context engineering) rather than large pyramids of commodity juniors. “Leaders also describe moving away from traditional linear staffing toward more autonomous or AI-assisted engineering models. However, we are also hearing from the large engineering teams the value of junior-level talent. So the diamond will not be pointy at the bottom but more like a standing pentagon. We see AI shifting from pilots to scaled, revenue-bearing platforms and managed services, often bundled into larger transformation deals (not sold standalone). At the same time, AI productivity is compressing some legacy areas, so traditional businesses face deflation unless providers move up to IP-led, AI-enabled transformation and managed services,” remarked Sharma.

But despite all the disruptions, growth in AI services is expected to continue as companies increasingly integrate AI into their operations, leading to larger and more complex deal sizes. This shift is driven by the demand for AI's capabilities in automating processes, enhancing decision-making, and providing predictive maintenance. As for other business segments, traditional businesses may face challenges in maintaining returns as they compete with the efficiency and innovation brought by AI-enabled services. Companies will need to adapt by incorporating AI to remain competitive and optimise their returns. Gartner has forecast that AI spending will grow by 47 per cent in 2026 to $2.6 billion as enterprises seek to achieve transformative value with AI.

Ashok Soota, Chairman and Chief Mentor, Happiest Minds, while talking to THE WEEK, expressed confidence in their AI-first initiative, which they have adopted. “As our Co-Chairman, Joseph Anantharaju and I have stated several times, we see AI as an opportunity and not a threat. We have not witnessed any pricing pressure. Productivity savings are passed on to our customers, and this only leads to an increase in volumes due to the large requirements,” Soota told THE WEEK.

He mentioned that the company had launched its AI First Initiative—the 11th strategic initiative which represents not merely an addition to the existing framework, but a strategic elevation. The AI first has reoriented the company's entire operating model, service delivery architecture, and client engagement philosophy around the primacy of artificial intelligence as a value-creation mechanism.

At the time of the AI First launch, the company communicated that it was observing rapid acceptance of its initiatives across the client base. Acknowledging the pace of change, the company had indicated it would undertake an evaluation of client feedback, pipeline metrics, market opportunities, and the expanded scope of its AI First offerings and provide an updated growth outlook. As per Soota, the company had also stated that this growth will establish a solid foundation for FY28, where it aspires to achieve 15 per cent growth.

What kind of specialised AI skill sets will IT services companies require? 

“As AI becomes foundational to enterprise transformation, IT heads must recalibrate their early-career talent strategies. Future-ready freshers will be distinguished by their fluency in AI or ML fundamentals, hands-on proficiency with core programming languages like Python, and adeptness in large-scale data analysis. Competency in building and operationalising AI models, as well as prompt engineering for GenAI, will set candidates apart. In addition, IT heads should prioritise candidates who demonstrate a commitment to continuous learning and adaptability, ensuring the organisation remains resilient amid rapid AI innovation,” pointed out Maity.

In addition to that, freshers will need strong foundations in data engineering, governance, and context pipelines, plus skills in agent or workflow orchestration, testing or validation, and secure deployment practices. “Context engineering and multi-agent orchestration show up as high-value work providers must build. Premiums for AI skills are already visible in rate cards,” pointed out Sharma.

But currently, the Indian IT services segment is facing market uncertainty due to geopolitical conditions, as the pressures are coming in from increased geopolitical uncertainty and market volatility, fuelled by rapid advances in technology and changing global power structures. As AI adoption accelerates worldwide, countries at the forefront of this shift are gaining both geopolitical and economic advantages.

“For India, where IT services account for 7–8 per cent of GDP, falling behind in AI innovation could have far-reaching effects on industry growth, employment, and currency stability. Ongoing geopolitical tensions and evolving supply chains are encouraging global clients to diversify their sourcing strategies, creating both new opportunities and challenges for Indian providers, especially given persistent infrastructure and regulatory constraints. Nevertheless, the industry continues to demonstrate resilience, with IT spending in India projected to reach $ 176.3 billion in 2026, a 10.6 per cent increase from 2025. Overall, the outlook for the sector remains optimistic, supported by strong demand and continued investment in digital transformation,” observed Maity.

But despite market apprehensions about a reduction in client spending, firms such as Gartner predict that client spending has not reduced, and that is a positive sign for the sector. In fact, it continues to rise. According to Gartner’s IT spending forecasts, total global IT spending is expected to grow from $5,563.8 billion in 2025 to $6,316.5 billion in 2026, reflecting an increase of over 10 per cent. This growth is largely driven by ongoing investments in AI infrastructure and software, as well as the rapid adoption of cloud and digital technologies. These trends highlight strong and sustained market demand, enabling organisations to move up the value chain and pursue greater innovation.

On the other hand, firms such as Forrester see AI shifting from pilots to scaled, revenue-bearing platforms and managed services, often bundled into larger transformation deals (not sold standalone). At the same time, AI productivity is compressing some legacy areas, so traditional businesses face deflation unless providers move up to IP-led, AI-enabled transformation and managed services.

Experts do agree that application development, application maintenance, traditional infrastructure operations and parts of business process management are precisely the layers where generative AI is now showing measurable productivity gains. That is roughly the at-risk slice of the industry book. The AI-amplified slice- data, cybersecurity, cloud and AI-native engineering- can grow at high single to low double digits. The shrinking part is also the part that historically funded the people pyramid, which is the structural problem. On top of that, client budgets in communications, retail and parts of manufacturing are flat to negative on discretionary spend, AI productivity savings are being demanded back rather than retained, and procurement-led vendor consolidation has returned. AI is reshaping IT services rather than just expanding the demand pie.

“CEOs I speak to are privately acknowledging that the same scope today translates to a smaller dollar value than a year ago, and requires more effort to deliver. That gap between (TCV) Total Contract Value and revenue is AI deflation in real time. Geopolitics, tariffs and a sluggish discretionary cycle are doing their share, but AI is the disruptor that explains why a bigger order book delivers smaller revenue growth, remarked Dev Chandrasekhar, partner at Transcendum, a valuations branding advisory.

This expert says that the client conversation has become paradoxical. “Clients now expect every input and every outcome to be AI-first, which is a higher bar in terms of capability. But because AI tools make DevSecOps and adjacent delivery functions cheaper and faster, those same clients believe the billing should reflect this. They want premium delivery at productised pricing. That is the squeeze,” added Chandrasekhar.

So faster work, fewer people, what has changed? 

The unit economics of delivery have shifted. TCS now talks of 12-16 week delivery cycles with AI. Infosys is reporting flat to marginally positive volume growth even as revenue grows in single digits, which is a polite way of saying headcount is no longer the lead indicator.

“The industry has spent two decades selling people-time as the primary unit of value. That meter is being replaced by an outcome meter, where a platform plus a smaller team delivers what a much larger team did before. The pressure is on the revenue line, not yet on margins, because vendors are capturing the productivity before passing it on. That changes when renewals of deals come up,” pointed out Chandrasekhar.

Currently, the expectation of IT services companies has changed from writing code to validating code written by AI assistants. “The future I would draw is closer to a triple structure. A narrower bottom of validators and prompt engineers. A thicker middle of solution architects, data engineers and AI builders. A still narrow top of partners and account leaders, but with a higher AI literacy than today's cohort holds. The implication for engineering campus recruitment, B-school placements and the broader employment compact in IT is significant and has not yet been fully priced in,” said Chandrasekhar.

Looking ahead, the outlook for the IT services segment remains positive despite current challenges. As organisations continue to prioritise digital transformation, investments in AI, cloud, and automation are expected to drive steady growth in the sector. “While short-term uncertainty may persist due to geopolitical tensions and economic volatility. We anticipate that IT spending will remain resilient, with significant growth projected over the next few years,” said Maity.

On the other hand, Forrester’s outlook at the beginning of 2026 was that it would be shaping up as a recovery year, but improvement depends on geopolitical shocks staying contained and on providers monetising AI via platforms, managed services, and new commercial models. “Expect uneven recovery: firms that shift from labour-arbitrage to AI assets plus domain depth will rebound sooner,” said Sharma.