Artificial intelligence is changing the economics of India’s information technology services industry at a time when enterprise technology buyers are becoming more focused on measurable productivity, lower delivery costs and faster business outcomes.
One of the most important changes is occurring in the cost of using AI itself. The cost of AI inference - the expense associated with querying a trained model - has fallen sharply at comparable levels of capability. Stanford University’s 2025 AI Index found that the inference cost for a model performing at approximately GPT-3.5 level on the MMLU benchmark fell from about $20 per million tokens in November 2022 to $0.07 per million tokens by October 2024, a reduction of more than 280 times. The report also found that inference prices had declined between nine and 900 times per year depending on the task. (Stanford HAI)
At the same time, AI is not making every part of technology cheaper. Gartner expects Indian organisations to spend $17.5 billion on public cloud services in 2026, up 28.1% from $13.7 billion in 2025. Gartner said demand for AI-ready infrastructure, including high-performance computing, GPUs, networking and scalable storage, is increasing cloud investment. (Gartner)
This creates a more complicated environment for Indian IT services companies. Lower AI unit costs can reduce the cost of performing certain software, support and automation tasks, but those efficiency gains are increasingly becoming part of customer negotiations.
A Reuters report published in August 2026 found that large Indian IT service providers were increasingly moving toward outcome-based contracts as clients sought lower prices and greater productivity. Persistent Systems CEO Sandeep Kalra told Reuters that some clients were asking for the same work at 25% to 30% lower cost, while also demanding faster delivery and higher productivity. (Reuters)
The result is a changing market in which AI can create new business opportunities while simultaneously putting pressure on traditional revenue models.
How AI Pricing Pressure Is Changing the IT Market
India’s technology sector remains large and diversified despite the changing economics of software services. NASSCOM estimated that India’s technology sector was expected to cross $315 billion in revenue in FY26, while direct technology-sector employment was projected to reach approximately 6 million, including a net addition of about 135,000 employees. NASSCOM also described FY26 as a period in which the industry was moving from scale-led growth toward greater emphasis on value, innovation and enterprise AI. (NASSCOM Community)
The pressure is emerging because clients increasingly have another reference point when negotiating technology contracts: what AI-assisted delivery makes possible.
Traditional IT services pricing often reflected the number of employees, hours, projects or service capacity required to complete work. AI-assisted software development, testing, documentation, service management and business-process automation can reduce the amount of manual effort required for some activities.
That does not mean every IT task becomes cheaper by the same amount. Complex transformations still require architecture, domain expertise, security controls, data management, integration, governance and human oversight.
However, the economics of repetitive work are changing.
Reuters reported in August that Indian IT providers are increasingly linking fees to measurable outcomes rather than hours worked. TCS Chief Executive K. Krithivasan told Reuters that roughly 80% of TCS contracts in its finance, human resources and other business-services segment were based on outcome-performance measures, approximately double the level since AI became mainstream in late 2023. (Reuters)
That shift matters because it changes what customers are purchasing. Instead of paying primarily for labour capacity, customers can increasingly negotiate around cost savings, productivity, service levels, faster delivery or specific business results.
NASSCOM has similarly identified a move away from FTE-based delivery toward outcome-based and risk-sharing models as AI productivity becomes more visible. (NASSCOM Community)
Impact on Indian IT Services Companies
The financial results of major Indian IT companies show that AI demand is growing, but the effect on revenue and margins is not uniform.
TCS
Tata Consultancy Services reported revenue of $7.624 billion in Q1 FY27, ended June 30, 2026, representing 2.7% year-on-year growth in US-dollar terms. Its operating margin was 24.0%, while quarterly total contract value reached $9.5 billion.
TCS also reported annualised AI revenue of $2.6 billion, up 13.6% sequentially. The company announced several AI-led transformation wins during the quarter, including an $800 million deal with SKF. (Tata Consultancy Services)
These figures indicate that AI is already producing substantial commercial activity for the company. At the same time, TCS management has acknowledged that AI-related downward pressure on revenue needs to be offset by new work. Reuters reported Krithivasan saying that the company had so far compensated for that pressure through additional business, while the longer-term issue would be how quickly new revenue could exceed revenue deflation. (Reuters)
Infosys
Infosys reported $5.082 billion in revenue for Q1 FY27, with constant-currency revenue growth of 2.4% year on year. Its operating margin was 21.1%, while large-deal total contract value reached $3.6 billion, with 61% classified as net new business.
AI represented 8.2% of Infosys' revenue in the quarter. CEO Salil Parekh said AI momentum was converting into revenue and highlighted Infosys Topaz and partnerships across the AI ecosystem. Infosys also said it was continuing to invest in AI, talent and platforms while focusing on productivity and operating leverage. (Infosys)
The company's results illustrate both sides of the AI transition: customers are purchasing AI-related services, but service providers are simultaneously investing in the technology and skills required to deliver them.
HCLTech
HCLTech reported $3.65 billion in revenue for Q1 FY27, up 3% year on year in US dollars and 2.6% in constant currency. Its EBIT margin was 16.9%.
The company's Advanced AI revenue reached $171 million, increasing 62.1% year on year in constant currency and 10.6% sequentially. HCLTech also announced plans to invest up to ₹3,500 crore to establish AI data centres. (HCLTech)
The figures show that AI is becoming a meaningful service category while also creating additional infrastructure investment requirements.
Wipro
Wipro's IT services revenue for Q1 FY27 was $2.6145 billion, up 1.0% year on year. Constant-currency IT services revenue increased 0.9%, while its IT services operating margin was 16.0%, down from the previous quarter and a year earlier.
At the same time, Wipro reported $1.626 billion in large-deal bookings, up 12.9% sequentially in constant currency. (Wipro)
Wipro is also building its AI capabilities. In June 2026, the company launched an Applied AI Center of Excellence for Anthropic's Claude models and said the initiative would integrate AI capabilities into its Wipro Intelligence stack. (Wipro)
The contrast between strong large-deal bookings and lower operating margins highlights the central industry issue: demand for transformation can grow while the cost of winning and delivering that work also changes.
Generative AI and Automation
Generative AI is increasingly becoming embedded in software engineering, cloud modernisation, service management, customer support, data operations and other technology functions.
TCS, for example, offers generative AI services through partnerships with Microsoft and Google Cloud and has developed AI-led approaches to application development and data modernisation. Its Agentic SDLC offering on Microsoft Azure uses generative and multi-agent AI for application modernisation, while its Google Cloud partnership includes an AI-powered data accelerator aimed at automating parts of legacy data migration and modernisation. (Tata Consultancy Services)
Persistent Systems is using AI-led platforms as part of its service strategy. For Q1 FY27, it reported $452.4 million in revenue, up 16.1% year on year, with an EBIT margin of 16.0% and total contract value of $1.146 billion. The company said its AI-driven platforms were being used to help clients reshape operating models and deploy intelligent enterprise capabilities. (Persistent Systems)
Coforge reported even stronger growth in Q1 FY27. Revenue rose 33% in US-dollar terms to $592.2 million, while EBIT margin reached 16.0%. The company said 86% of revenue came from AI-led engineering, data and cloud services and attributed part of its margin improvement to AI deployment in client delivery and internal operations. (Coforge Newsroom)
These examples show that AI is not simply being sold as a standalone consulting product. It is increasingly being embedded inside existing engineering, cloud and managed-service offerings.
Rising Competition and Client Expectations
As AI lowers the amount of human effort required for some technology tasks, the advantage associated with having a very large workforce can become less decisive for certain projects.
Reuters reported that smaller and mid-sized IT service providers were winning business by moving rapidly, deploying senior professionals and offering more flexible commercial terms. Persistent and Coforge were among the companies highlighted for sustained double-digit growth in the April-June 2026 period, while several larger providers recorded more modest growth. (Reuters)
Competition also comes from outside the traditional Indian IT services model.
Hyperscalers such as Microsoft, Google Cloud and AWS increasingly offer cloud, AI infrastructure and development tools directly to enterprises, while global AI companies provide foundation models and related platforms. Specialist AI providers and AI-native software companies can also address individual workflows without requiring a large traditional outsourcing engagement.
This creates a more fragmented value chain.
An enterprise can purchase infrastructure from a cloud provider, foundation-model access from an AI company, specialised software from an AI-native vendor and integration or managed services from an IT provider.
Indian IT companies therefore have to demonstrate value beyond access to engineers alone. Domain expertise, systems integration, cybersecurity, governance, data management, transformation consulting and the ability to deploy AI securely at enterprise scale become more important differentiators.
Pricing, Margins and Revenue Models
The pricing issue is particularly visible in software development and application-related services, where automation can affect the amount of manual work required.
A June 2026 industry report published by Moneycontrol, citing Greyhound Research, said Indian IT companies experienced 5% to 15% revenue compression in FY26 in areas where AI-led productivity gains were visible and measurable. The report characterised the effect as AI-related deflation and noted that customers were seeking to renegotiate contracts. (Moneycontrol)
That figure should be treated as an industry-research estimate for specific delivery areas, not as a universal reduction in IT-service prices.
At the broader industry level, CRISIL Ratings expects Indian IT-services revenue growth to remain subdued at roughly 1% to 3% over the near term as AI disruption, weak discretionary spending and geopolitical uncertainty affect demand. CRISIL said AI-native solutions were intensifying pricing pressure and contributing to deal renegotiations. It also expects operating margins to remain around 22% to 23% for the broader sector this fiscal, although that cushion could narrow later as revenue pressure, talent costs and AI investment continue. (CRISIL)
The pressure does not necessarily mean that every contract becomes smaller.
A different model is emerging in which providers accept lower labour intensity but attempt to capture value through larger transformation programmes, recurring platforms, outcome-based fees and specialised consulting.
Persistent's Q1 FY27 growth and Coforge's high AI-led revenue share provide examples of providers attempting to increase the value captured from AI-enabled engineering and transformation rather than relying only on traditional staffing models. (Persistent Systems)
Workforce and Skill Changes
The workforce effect of AI is becoming visible primarily through changing skill requirements and hiring priorities rather than through a single industry-wide employment outcome.
NASSCOM expects technology-sector direct employment to reach approximately 6 million in FY26, with net additions of around 135,000 employees. At the same time, its 2026 strategic review says hiring is shifting from volume toward skill mix as AI-driven productivity becomes more significant. (NASSCOM Community)
CRISIL also expects net headcount additions to remain muted as companies emphasise automation, higher employee utilisation and selective hiring for AI-related skills. (CRISIL)
This creates greater demand for capabilities such as AI engineering, data architecture, cloud infrastructure, cybersecurity, AI governance, domain-specific implementation and software engineering supported by AI tools.
Major companies are investing accordingly.
TCS says it has built AI and cloud capabilities around its enterprise transformation offerings, while Infosys has emphasised continued employee reskilling as part of its AI strategy. Infosys said in its July 2026 results announcement that it remained committed to reskilling employees across levels. (Tata Consultancy Services)
The workforce model is therefore becoming more complicated. AI can reduce the manual effort needed for certain assignments while increasing demand for employees who can design, supervise, integrate and secure AI-enabled systems.
Industry and Expert Views
Industry assessments increasingly describe AI as both a productivity technology and a challenge to the traditional economics of IT services.
CRISIL Senior Director Anuj Sethi said in July 2026 that AI was no longer only a productivity lever and was beginning to challenge the traditional revenue model by increasing pricing pressure and triggering deal renegotiations. (CRISIL)
Everest Group CEO Jimit Arora told Reuters that the current market gives customers substantial negotiating leverage as service providers compete for a limited pool of technology spending. (Reuters)
At the same time, the demand side of the market remains active.
Gartner forecasts total public-cloud spending in India at $17.5 billion in 2026, while IDC's India outlook indicates that organisations are moving from GenAI experimentation toward broader applications in productivity, development and operations. IDC says AI-related spending in India was projected to reach $6 billion by 2027, representing a 33.7% CAGR from 2022 to 2027, while 76% of Indian enterprises were already working on GenAI proofs of concept or had investment plans. (Gartner)
The combination suggests that the market is not simply shrinking because of AI. Rather, spending is being redirected toward different types of technology, with customers becoming more demanding about the commercial value generated by that spending.
Key Challenges and Opportunities
For Indian IT services companies, the central challenge is balancing productivity gains with commercial value.
If AI allows a provider to complete the same amount of work using fewer labour hours, customers may seek to capture part of that saving through lower contract prices. That can pressure revenue per employee and make traditional volume-driven models harder to sustain.
There are also significant costs on the provider side.
AI systems require cloud infrastructure, data preparation, model access, security controls, specialised talent, governance frameworks and ongoing investment. Gartner's forecast for rapidly rising cloud spending in India illustrates that the infrastructure side of the AI economy is still expanding even while the cost of individual model queries can decline. (Gartner)
Cybersecurity and governance add another layer. Enterprise customers handling financial, healthcare, industrial or sensitive information may require strong controls over data access, model behaviour, auditability and system security.
There are opportunities as well.
AI can help Indian IT providers move into higher-value consulting, AI engineering, cloud transformation, data modernisation, cybersecurity and managed AI operations. It can also enable providers to take on larger workloads without a proportional increase in manual effort.
TCS' AI revenue, HCLTech's Advanced AI growth, Infosys' AI revenue share, Persistent's AI-led engineering approach and Coforge's high AI-related revenue contribution demonstrate the variety of ways companies are attempting to participate in this market. (Tata Consultancy Services)
Conclusion
AI pricing pressure is becoming a structural issue for India's IT services industry, but the change is more complex than a simple story of falling technology costs.
AI inference costs have fallen dramatically at comparable performance levels, making some workloads cheaper to operate. At the same time, spending on AI-ready cloud infrastructure, computing capacity, data platforms and specialised technology is increasing. (Stanford HAI)
The economic effect is increasingly visible in customer contracts. Buyers are seeking measurable productivity improvements, shorter delivery cycles and greater value from technology budgets. Reuters' reporting shows that outcome-based commercial models are gaining ground, while industry research points to pressure on pricing and revenue in areas where AI productivity is easiest to measure. (Reuters)
Indian IT services companies are responding by expanding generative AI and automation capabilities, investing in cloud and AI infrastructure, forming partnerships with major technology platforms, building proprietary tools and shifting toward consulting and outcome-oriented services.
The financial results of Q1 FY27 show that these strategies are producing new AI-related revenue opportunities, although growth and margins remain uneven across companies. TCS reported annualised AI revenue of $2.6 billion, Infosys said AI represented 8.2% of revenue, HCLTech reported Advanced AI revenue of $171 million, and Wipro continued to secure large contracts while facing margin pressure. (Tata Consultancy Services)
The industry is consequently moving toward a model in which technological capability, pricing discipline, domain expertise, AI-skilled talent and measurable business outcomes matter alongside workforce scale.
AI is not eliminating the need for IT services. It is changing what clients expect to pay for, what providers need to deliver and how value is measured.
Further reading and useful links
Reader questions
Frequently asked questions
How is AI affecting pricing in India's IT industry?
Declining AI inference costs and increased productivity are driving clients to demand lower prices and faster delivery, leading IT providers to shift toward outcome-based contracts rather than traditional hourly or staffing models.
What is the shift toward outcome-based contracts?
Instead of paying primarily for labor capacity or hours worked, customers increasingly negotiate contracts around cost savings, productivity, service levels, and specific business results.
How are major Indian IT companies performing with AI revenue?
Major providers are seeing rapid growth in AI service lines - such as TCS reporting $2.6 billion in annualized AI revenue and HCLTech reaching $171 million in Advanced AI revenue in Q1 FY27 - while simultaneously managing margin pressures and pricing negotiations.
Are cloud investments increasing despite falling AI costs?
Yes. While the cost of querying AI models has dropped dramatically, Gartner forecasts that public cloud spending in India will rise to $17.5 billion in 2026 to support AI-ready infrastructure like high-performance computing, GPUs, and scalable storage.
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