- Indian IT stocks have slumped 20% in February, shaking confidence.
- AI can automate core outsourcing services, but also opens new revenue streams.
- Macro headwinds – weaker US/EU demand, delayed Fed cuts – amplify the sell‑off.
- Valuations remain reasonable; selective buying on pullbacks may deliver outsized returns.
- Diversify between Indian IT leaders, AI‑enabled US tech giants, and infrastructure plays.
You ignored the AI‑risk warning on Indian IT services – and your portfolio paid the price.
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Why the Nifty IT Index Is Down 20%: Macro & AI Pressures
The Nifty IT index has fallen roughly one‑fifth this month, dragging marquee names such as TCS, Infosys, Tech Mahindra, HCL Technologies and Coforge into the red. Two forces are colliding. First, the macro environment – a slowdown in US and European IT spend, tepid Fed‑rate‑cut expectations and a cautious corporate‑budget outlook – has already trimmed deal flow. Second, a wave of AI‑driven automation narratives suggests that traditional code‑development, testing and legacy‑system support could be supplanted by generative models like Anthropic’s Claude Code.
When investors hear that an AI system can rewrite COBOL in hours, the instinct is to fear an existential threat to the very services that have funded the Indian IT boom for three decades.
AI’s Double‑Edged Sword: Which Indian IT Services Face Real Risk?
Not every line‑item on an Indian IT balance sheet is equally exposed. Sub‑segments that rely heavily on repetitive coding, test‑automation and contract‑review are most vulnerable. According to Appreciate’s CEO Subho Moulik, the three diagnostic questions – revenue share from pure application services, presence of proprietary AI platforms, and pricing model (hourly vs outcome‑based) – separate potential survivors from bleed‑outs.
Conversely, firms that have already embedded AI into cloud‑native offerings, data‑analytics suites, or outcome‑based managed services are positioned to capture higher‑margin, scalable revenue. These players can shift from a cost‑center narrative to a value‑creation story, leveraging AI as an enabler rather than a replacement.
Sector‑Wide Trends: Revenue Outlook, NASSCOM Forecast, and Global Comparisons
NASSCOM projects a 6.1% YoY revenue growth to $315 billion in FY26, breaking the $300 billion barrier for the first time. The optimism rests on AI‑driven modernisation of enterprise stacks, which, despite compressing legacy work, expands demand for cloud migration, cybersecurity and data‑platform services.
Globally, HSBC argues that AI will be embedded within software platforms, not eradicate them. This mirrors the broader tech‑industry shift where hardware‑led AI growth (chips, data‑centres) is giving way to service‑led deployment in enterprises.
Competitor Landscape: How Tata, Infosys, and Emerging Players Differ
Tata Consultancy Services (TCS) and Infosys have pursued aggressive cloud‑partner strategies with Microsoft, Google and AWS, building AI‑ready solution suites. Their balance sheets boast strong cash reserves and diversified client bases across banking, pharma and retail, reducing single‑region exposure.
Mid‑tier players like Tech Mahindra and HCL are accelerating AI pilots but still carry a higher proportion of traditional outsourcing contracts. Coforge, with a niche focus on legacy‑system modernisation, may feel the short‑term squeeze more acutely.
Emerging entrants that specialize in AI‑centric SaaS – for example, companies offering AI‑powered automation platforms – are beginning to capture attention from global enterprises, creating a potential upside tail for investors willing to look beyond the classic “big‑four”.
Technical Lens: Understanding AI‑Enabled Automation vs Traditional Outsourcing
Generative AI coding refers to large language models that can produce, test and debug software snippets with minimal human input. This reduces the labour‑intensive portion of the value chain, compressing margins for firms that price by the hour.
Outcome‑based pricing shifts the contract from a cost‑plus model to a performance‑linked model, where the vendor is paid on realized business outcomes (e.g., reduced time‑to‑market). This aligns incentives and can command premium fees, insulating providers from pure labor‑rate pressure.
Understanding these distinctions helps investors evaluate whether a company’s revenue mix is moving from a low‑margin, labor‑heavy base to a higher‑margin, platform‑driven model.
Investor Playbook: Bull vs Bear Cases for Indian IT and US Tech Exposure
Bull Case – AI integration accelerates, and Indian firms successfully transition to platform‑as‑a‑service and outcome‑based contracts. Valuations remain attractive (EV/EBITDA 10‑12x) while earnings guidance upgrades, delivering a 30‑40% upside over the next 12‑24 months.
Bear Case – AI automation erodes core services faster than firms can re‑skill, leading to margin compression and delayed earnings. Persistent macro softness in the West drags revenue, pushing the index below 12‑month lows and exposing investors to a 20‑25% downside.
Strategic allocation recommendation:
- Core Tier: AI‑enablers – cloud infrastructure (AWS, Azure partners), semiconductor exposure (Nvidia‑like stocks), and data‑platform leaders.
- Secondary Tier: High‑growth software firms embedding AI into workflows (e.g., ServiceNow, Snowflake).
- Tertiary Tier: Select Indian IT leaders with proven AI roadmaps (TCS, Infosys) – enter on pullbacks, target a 5‑10% portfolio weight.
Maintain a three‑year horizon to ride execution risk and monitor three key metrics: (1) share of revenue from outcome‑based contracts, (2) progress on proprietary AI platforms, and (3) exposure to cloud/hyperscaler partners. Adjust allocations as firms demonstrate tangible AI monetisation.