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By Alpha Research
Feb 25, 2026
WHAT’S HAPPENING IN ARTIFICIAL INTELLIGENCE
Artificial Intelligence is currently undergoing a large-scale transition from experimental technology to core business infrastructure. Over the past three years, AI has moved beyond limited use cases such as chatbots and analytics into enterprise-wide deployment across software development, customer operations, financial analysis, and automation.
This shift has been enabled by advances in computing power, the availability of large datasets, and improvements in model architectures such as neural networks and transformer-based systems. These technologies allow AI systems to analyse large volumes of information, generate human-like responses, and automate complex tasks that previously required skilled human labor.
One of the clearest indicators of this structural shift is the sharp increase in capital expenditure by global technology companies. Firms such as Microsoft, Amazon, Alphabet, and Meta are investing heavily in data centers, AI chips, and computing infrastructure required to train and operate large AI models.
Capital expenditure by Microsoft, Amazon, Alphabet, and Meta has risen sharply over the past few years and is projected to approach approximately $600 billion in 2026, compared with less than $100 billion annually before 2020. This scale of increase reflects a sustained infrastructure buildout rather than a short-term spending cycle.
Modern AI systems require massive computing power. They must be trained on enormous datasets using advanced chips and then run continuously on large-scale data centers. This means AI is not just a software upgrade it is a full-scale infrastructure built out involving semiconductors, cloud networks, data centers, and energy capacity.
Spending on this infrastructure is rising rapidly because companies are moving beyond AI experiments. AI is now being used in coding, customer support, fraud detection, data analysis, content creation, and business automation. It is becoming part of daily operations, not just a side project.
But AI is also changing the economics of work. when AI can perform tasks previously done by skilled employees, costs fall. Companies may hire fewer people, vendors may lose pricing power, and wages in certain roles may come under pressure. Layoffs are the visible effect.
The less visible and potentially more important effect is cost reduction. If the cost of intelligence drops, the cost of running a business falls. Smaller companies gain access to tools that were once expensive. Barriers to entry decline. Starting a business becomes easier. Productivity improves.
When something becomes cheaper, economies usually adjust in one of three ways:
1) People use more of it,
2) New industries are created around it,
3) Savings are spent elsewhere.
If lower AI costs lead to more entrepreneurship, faster innovation, and broader access to services, overall economic growth can continue even if the type of jobs change. This would mean higher output with lower costs.
The risk appears only if automation replaces income faster than new demand is created. If businesses cut jobs but demand does not expand, income pressure could slow consumption.
AI has clearly entered a large-scale deployment phase. The infrastructure buildout is real. The adoption is real. The long-term outcome will depend on whether cheaper intelligence expands demand fast enough to offset job displacement.
That is the real debate not whether AI is growing, but how the economy adapts to it.
SPOTLIGHT ON ANTHROPIC’S CLAUDE: A STRUCTURAL INFLECTION POINT
Anthropic has emerged as one of the most valuable and fastest-growing companies in the global AI ecosystem. In February 2026, the company raised $30 billion in funding at a $380 billion valuation, making it more valuable than the entire Nifty IT index, whose combined market capitalisation has fallen to approximately $296 billion, down from a peak of $475 billion in January 2022. This valuation gap highlights the rapid shift in investor capital from traditional IT services toward AI-native companies.
Anthropic’s growth has been supported by strong enterprise adoption of its Claude models, with the company reaching an estimated $14 billion annualized revenue run-rate, representing more than 10-fold growth over the past three years. Its coding-focused tools, such as Claude Code, and agent-based enterprise solutions have enabled automation of software development, data analysis, and operational workflows, reducing dependence on labor-intensive service models.
The company’s recent rollout of agentic AI tools and enterprise plugins has intensified disruption concerns. These systems can independently execute complex tasks such as coding, financial analysis, and business process automation, significantly improving productivity while reducing human intervention. As a result, investors have reassessed the long-term earnings potential of traditional software and IT services firms.
The market reaction has been immediate. Indian IT majors including TCS, Infosys, and others declined ~15%-25% during the last 3 weeks, contributing to an estimated $70 billion erosion in market value across the sector. This reflects investor concerns that AI-driven automation could compress billing hours, reduce entry-level hiring demand, and structurally alter the outsourcing-driven IT services model.
Overall, Anthropic’s rapid rise, scale of valuation, and enterprise adoption demonstrate that AI is evolving from a productivity enhancement tool into a core execution layer, with significant implications for software companies, IT services firms, and global capital allocation.
INDIAN IT SECTOR DOWNTURN: UNDERSTANDING THE MARKET REACTION
The Indian IT sector has experienced a significant market correction in recent months, driven primarily by investor concerns that AI-driven automation could disrupt its traditional manpower-based business model.
Source: Groww, as on 25th Feb 2026
To understand this concern, it is important to recognize the structural nature of Indian IT.
India’s IT services industry remains a structural pillar of the economy. The sector generates approximately $280-285 billion in annual revenue, contributes 6.5-7.5% to national GDP, accounts for nearly 25-30% of total exports, and provides direct employment to more than 5.5 million people.
Within the industry, IT Services form the core segment, contributing 48% of total revenue (approximately $137.1 billion). At the same time, Engineering Research & Development (ER&D) and Business Process Management (BPM) together account for 39% of sector revenue, reflecting a gradual shift toward higher-value, specialised, and digitally driven service offerings aligned with global transformation demand.
The rise of advanced AI models such as Anthropic’s Claude is expected to impact these segments unevenly. Business Process Management faces the highest disruption risk, as agentic AI systems can automate repetitive tasks such as customer support, document processing, and compliance workflows.
Traditional IT services, including software development, testing, and maintenance, also face structural pressure, as AI coding tools improve productivity and reduce reliance on large engineering teams. In contrast, Engineering R&D remains relatively more resilient, as it involves complex, domain-intensive work where AI currently acts as a productivity enabler rather than a full replacement. This indicates that AI is likely to reshape the sector’s growth model, accelerating the shift from labor-intensive services toward higher-value, specialised engineering and AI-integrated offerings.
HISTORICAL STRUCTURAL ADVANTAGES THAT ENABLED INDIA’S IT DOMINANCE
This allowed India to become the world’s largest technology execution engine, responsible for maintaining enterprise software systems, managing cloud infrastructure, writing and testing code, and enabling digital transformation for global corporations.
However, this model is fundamentally labour-linked. Revenue has historically been correlated with the number of engineers deployed and billable hours. Artificial intelligence disrupts this equation by increasing productivity per employee. Projects that previously required 100 engineers may now require significantly fewer personnel, reducing incremental hiring demand and altering traditional pricing models. This has triggered concerns about long-term growth and margins, resulting in valuation compression across Indian IT stocks.
The recent launch of advanced AI systems such as Anthropic’s Claude has intensified these concerns, as these systems directly target application development and enterprise automation core revenue areas for Indian IT firms. However, these concerns must be viewed in proper structural context.
STRUCTURAL REALITY: GLOBAL ENTERPRISE TECHNOLOGY SPENDING IS NOT DISAPPEARING
Global enterprise software spending currently stands at approximately $300–350 billion annually, with North America and Europe accounting for nearly $160–250 billion. When combined with IT services and cloud infrastructure, total enterprise technology spending exceeds $5 trillion per year, underscoring the scale of systems that power modern businesses.
Despite rapid progress in artificial intelligence, this technology foundation cannot be replaced overnight. Large enterprises operate complex environments built over decades, involving legacy systems, regulatory requirements, and deeply interconnected workflows. These systems run critical functions from financial operations to supply chains and require stability, reliability, and controlled transformation.
As a result, AI is being integrated into existing infrastructure rather than replacing it entirely. This integration requires specialised expertise in system architecture, data management, cybersecurity, and operational deployment areas where IT services firms remain essential.
Rather than eliminating demand, AI is fundamentally reshaping it. The focus is shifting away from labor-intensive maintenance toward higher-value services such as AI integration, enterprise modernisation, and intelligent automation. This marks a structural evolution in the IT services model, as the role of service providers transitions from manpower suppliers to technology integration partners.
EVOLUTION OF INDIAN IT: CONTINUOUS ADAPTATION TO TECHNOLOGICAL DISRUPTION
Indian IT has consistently evolved through multiple technological disruptions.
Today, the industry is transitioning toward artificial intelligence integration, digital platforms, and automation services.
Each technological disruption initially created fear of job loss and industry decline. However, history consistently demonstrates that productivity-enhancing technologies ultimately expand economic activity.
Artificial intelligence is likely to follow a similar trajectory.
US TECHNOLOGY CORRECTION: TRANSITION FROM HYPE TO MONETIZATION
The U.S. technology sector differs significantly from Indian IT services in its business model and value creation. U.S. technology companies such as Microsoft, Apple, Nvidia, Alphabet, and Amazon operate as product and platform owners. They develop proprietary software, cloud infrastructure, semiconductors, and digital ecosystems, generating recurring revenue through subscriptions, licensing, advertising, and hardware sales. This ownership-driven model enables them to maintain strong pricing power, higher margins, and direct exposure to technological innovation.
In contrast, Indian IT companies such as TCS, Infosys, and HCL Technologies primarily operate as service providers. They help global enterprises implement, manage, and maintain technology systems, including cloud migration and software support. Their revenues depend on client IT spending and technology adoption cycles, rather than owning the underlying platforms. As a result, U.S. technology companies are the primary creators and monetizers of AI and digital infrastructure, while Indian IT companies benefit indirectly by supporting global technology deployment.
RECENT CORRECTION IN U.S. TECHNOLOGY: A ROTATION, NOT A COLLAPSE
U.S. technology stocks delivered strong returns in 2025, driven by optimism around artificial intelligence and robust earnings growth. However, 2026 has started on a weaker note, with several large-cap technology companies experiencing corrections as markets reassess valuations and the impact of AI disruption.
Following strong gains in 2025, valuation multiples across the U.S. technology sector expanded significantly, driven by optimism around artificial intelligence and future earnings growth. P/E multiples are now adjusting toward more sustainable levels. This repricing reflects normalization after a period of strong outperformance rather than a deterioration in underlying fundamentals.
Both the S&P 500 and Nasdaq remain above their 10-year average P/E ratios S&P 500 at 21.9 versus 15.2, and Nasdaq at 26.5 versus 18.5 reflecting elevated expectations for AI-driven revenue growth. While valuations are high, the adjustment in multiples suggests the market is now demanding clearer evidence of earnings delivery before further expansion.
Meanwhile, technology companies are investing heavily in AI infrastructure, including data centers, semiconductors, and computing capacity. These investments are expected to drive future revenue growth, though they may temporarily weigh on margins and earnings as the benefits materialize over time.
OUTLOOK FOR THE U.S. TECHNOLOGY SECTOR
The U.S. technology sector remains in a strong structural growth phase, driven primarily by artificial intelligence and cloud infrastructure investment. Despite recent volatility, this correction should be viewed in the context of the strong rally seen in 2023-2025 and reflects a period of adjustment rather than a structural deterioration in the sector.
The most important trend is the unprecedented scale of AI infrastructure spending. Major U.S. hyperscalers, including Amazon, Microsoft, Google, Meta, and Oracle are projected to spend over $700 billion in capital expenditure in 2026, representing more than 60% growth, as they expand data centers and computing capacity to support AI workloads. This level of investment highlights the urgency and long-term commitment toward AI development.
This is already driving strong growth across the broader ecosystem. Global semiconductor industry revenue is expected to grow 24% in 2026, supported by rising demand for AI chips, servers, and memory, with supply remaining constrained and order visibility extending multiple years.
At the same time, enterprise adoption of AI is accelerating, with over 120,000 enterprises using AI platforms such as Google Gemini and millions of paid users on Microsoft Copilot, indicating that AI is moving from experimentation to large-scale commercial deployment.
Overall, the U.S. continues to dominate the global technology landscape due to its leadership in cloud computing, semiconductors, and digital platforms. The scale of infrastructure investment, strong enterprise adoption, and sustained demand for computing power support a positive long-term outlook, with AI expected to remain the primary growth driver for the sector.
POSITIONING INDIA IN THE NEXT PHASE OF THE GLOBAL TECHNOLOGY CYCLE
India occupies a unique and strategically important position in the global AI transition. While the United States and China currently lead in foundational AI model development and semiconductor manufacturing, India holds a strong structural advantage in enterprise AI deployment, integration, and large-scale implementation.
India has over 5.4 million software professionals and accounts for approximately 16% of the global AI talent pool, making it the second-largest base of AI developers globally. This positions India as a key execution hub for enterprise AI adoption.
India is also rapidly expanding its AI infrastructure. The country’s data center capacity is projected to grow from approximately 1.5 GW currently to over 9 GW by 2030, supported by significant investments from hyperscalers such as Amazon, Microsoft, and Google. At the same time, leading Indian IT companies are investing aggressively in AI capabilities TCS has trained over 350,000 employees in AI, Infosys has launched its Topaz AI platform with over 250 enterprise engagements, and Wipro has committed $1 billion toward AI investments.
India’s startup ecosystem further strengthens this position, with over 7,000 AI startups, supported by government initiatives such as the Rs. 10,300 crore IndiaAI Mission, aimed at building national AI infrastructure and capabilities.
This positions India not as the primary creator of foundational AI models, but as one of the world’s largest AI deployment and integration economies. This distinction is critical, as a significant portion of AI value creation will occur in enterprise implementation, system integration, and infrastructure deployment areas where Indian IT companies possess strong structural advantages.
The recent correction in Indian IT stocks reflects a structural transition rather than a structural collapse. AI-led productivity gains may moderate traditional manpower-driven growth in the near term, but they are also shifting demand toward higher-value services such as AI integration, automation design, cloud migration, data engineering, cybersecurity, and enterprise transformation.
As global enterprises accelerate AI adoption with annual AI spending projected to exceed $500 billion by 2030 Indian IT companies remain well positioned to benefit, provided they successfully move up the value chain and adapt their service models to this evolving technology landscape.
Best Regards
Sakshi Rawat | Neeru Seal
Team Alpha Capital
Disclaimer: The information on this document is provided for information purpose only and is available in the public domain. It does not constitute any offer, recommendation. The views expressed by the Alpha Capital Research are based on current market conditions and information available publicly
