- Infosys lost 17% in February, its steepest monthly drop since April 2022.
- AI‑driven code‑generation fears are denting sentiment across the entire Indian tech sector.
- Domestic mutual funds face a notional ₹44,400‑crore loss; FIIs still hold the majority stake.
- Self‑built software accounts for only 14% of spend—far below 1990s levels—leaving vendors indispensable.
- Motilal Oswal sees AI as a revenue catalyst, not an existential threat.
You missed the warning signs on Infosys, and your portfolio may be paying the price.
Why Infosys's February Slide Signals a Sector‑Wide AI Reckoning
Infosys closed at ₹1,365.90 on Feb 16, marking four straight sessions of decline and a cumulative 9% loss. The broader Indian IT index has mirrored this trend, erasing billions of market value since the start of the month. The catalyst? Growing investor anxiety that generative AI tools—like Anthropic’s legal‑AI offering—could enable enterprises to write code internally, shrinking the addressable market for traditional outsourcing firms.
While analysts argue that the impact will be gradual, the market’s reaction is immediate because AI represents a potential structural shift. In finance, transportation, and logistics, firms are already piloting AI‑assisted development pipelines, prompting a re‑pricing of vendor exposure.
How Competitors Like TCS and Wipro Are Positioning Against In‑House Coding
Infosys is not alone. Tata Consultancy Services (TCS) and Wipro have both announced AI‑enabled consulting platforms that embed their services into client‑owned environments. By offering end‑to‑end integration, cybersecurity, and performance‑optimisation, they aim to lock in revenue streams that pure code‑generation cannot replace.
- TCS launched “TCS‑AI Suite,” a managed‑service layer that automates testing and deployment, reducing the need for clients to build internal DevOps capabilities.
- Wipro is betting on its “Holmes” AI engine to provide predictive maintenance for legacy applications, a service that internal teams struggle to replicate.
- Both firms have increased R&D spend by roughly 12% YoY, signaling confidence that AI can be a differentiator rather than a disruptor.
These moves suggest that the competitive edge will shift from pure coding to ecosystem integration, a space where large‑scale vendors still hold a moat.
Historical Parallel: The 2020 Cloud Migration Wave and Its Impact on IT Services
When cloud adoption accelerated in 2020, skeptics predicted the death of traditional data‑center services. Instead, vendors that pivoted to hybrid‑cloud consulting captured new revenue streams. Infosys, TCS, and Wipro collectively added over $5 billion in cloud‑related services in FY 2021, offsetting the slowdown in legacy maintenance contracts.
The lesson is clear: technology disruptions often reshape the value chain rather than eliminate it. AI may follow the same trajectory—initially eroding low‑margin coding work, then opening higher‑margin advisory and integration opportunities.
Decoding the Numbers: What a 14% Self‑Built Software Share Means for Vendors
Self‑built software now represents just 14% of total software spend, a stark contrast to the 35‑40% share of the 1990s when in‑house development was the norm. This gap reflects two realities:
- Enterprises still lack the talent and governance frameworks to manage complex, mission‑critical applications.
- Vendor ecosystems provide bundled services—security, compliance, uptime guarantees—that are difficult to replicate internally.
Consequently, even if AI drives a modest increase in self‑built adoption to 20% over the next three years, vendors will still command roughly 80% of the spend, preserving a sizable revenue base.
Investor Playbook: Bull vs. Bear Cases for Infosys Post‑AI Shock
Bull Case
- AI becomes a revenue‑accretive add‑on: Infosys monetises its own AI platforms, boosting margins.
- Continued strength in digital transformation contracts offsets any erosion in pure coding work.
- Domestic mutual funds rebalance, providing a buying cushion as valuations dip below ₹6 lakh crore.
Bear Case
- Rapid adoption of in‑house AI tools compresses top‑line growth faster than anticipated.
- Margin pressure from higher R&D spend without commensurate pricing power.
- Further sentiment‑driven sell‑offs could push the stock below ₹1,200, triggering stop‑loss cascades.
For the prudent investor, a phased approach works best: hold a core position to capture upside from AI‑enabled services, but keep a disciplined stop‑loss near ₹1,250 to protect against a deeper correction.