Technology: AI - Newspaper Summary

 The sources highlight that Technology, AI, and Digital transformation in Q2 FY26 were central to both Indian and global business strategies, characterized by massive capital investment into AI infrastructure, a fierce competition for digital supremacy in consumer markets, and strategic moves by IT firms to address valuation gaps and fund future technologies like Generative AI.

I. The Global AI Arms Race and Capital Investment

Global technology giants escalated their spending on Artificial Intelligence (AI) infrastructure, fueling concerns about mounting capital expenditure and setting high market valuation benchmarks.

A. Massive AI Investment and Financial Pressure

Major US tech firms reported soaring capital expenditure, primarily driven by the need to build infrastructure for developing and running AI models.

• Nvidia's Dominance: Nvidia reached an unprecedented $5 trillion market capitalization (as of October 29) after crossing the $4 trillion mark just three months prior. This surge was fueled by optimism in the AI ecosystem and the CEO's projection of $500 billion in AI chip orders.
• Microsoft's Spending Spree: Microsoft’s AI infrastructure spending soared to a record of nearly $35 billion in the September quarter, marking a 74% jump year-on-year in capital outlay. Investors expressed concern about the mounting costs of sustaining the AI boom and the pressure on Big Tech to show appropriate returns on this massive capital base. Microsoft secured a 27% stake in OpenAI, valued at $135 billion, which also grants it a cut of sales and access to intellectual property.
• Alphabet (Google) Investment: Google reported a record $102.3 billion in quarterly revenue, financing robust AI spending. The company expects its capital expenditures for the year to reach $91 billion to $93 billion (up from $52.5 billion in 2024), with a substantial increase projected for the next year, primarily directed toward building data centers for AI models. Google’s AI model, Gemini, reported over 650 million monthly users, with queries tripling since Q2.
• OpenAI's IPO Ambition: OpenAI is laying the groundwork for an Initial Public Offering (IPO) that could value the company at up to $1 trillion, potentially making it one of the biggest IPOs of all time. The filing is being considered as soon as the second half of 2026.
• Memory Chip Demand: The volatile memory-chip industry entered an extended boom period thanks to the AI business, with players like Samsung and SK Hynix enjoying surging demand for specialized products, particularly High-Bandwidth Memory (HBM), which is targeted for use in training AI models. DRAM, a major memory chip type, is estimated to bring in more than four times the industry-wide revenue next year compared to the trough in 2023.

II. Indian IT and Fintech Strategy: Valuation and Transformation

In India, the digital landscape was characterized by IT majors exploring strategic listings to resolve valuation disparities, while fintechs focused on IPOs to fund aggressive expansion and diversification into full-stack platforms.

A. IT Services and the Generative AI Mandate

The sources highlighted a significant valuation gap between Nasdaq-listed IT services firm Cognizant and its Indian peers, driving strategic exploration of an India listing.

• Valuation Arbitrage: Cognizant, despite earning more revenue than Infosys in the previous fiscal year, is valued at barely half its peer ($35.01 billion vs. $70.5 billion market cap). Cognizant trades at a P/E ratio of 16.59, compared to 18-25 for Indian peers like TCS, Infosys, HCL Technologies, and Wipro.
• Strategic Imperative: Cognizant is exploring a potential primary offering and a secondary listing in India to chase higher valuations and access India-centric funds. A crucial reason for the India listing plan is to secure fresh financial flexibility to invest in AI platforms, automation, and upskilling, as Generative AI compresses margins across the IT services sector.
• Growth Segments: Cognizant’s Financial Services vertical accelerated discretionary spending, moving "from experimentation to enterprise-grade AI". Its Business Process as a Service (BPaaS) platform, TriZetto, in the healthcare segment, also contributed strongly to growth.

B. Fintech Innovation and Digital Infrastructure

Indian fintech companies leveraged digital infrastructure (Aadhaar, UPI) for strategic growth and innovation, while the broader financial market contemplated new digital frontiers.

1. Full-Stack Wealth Management: Groww utilized its impending ₹6,632.3 crore IPO to fund its transition into a full-stack wealth platform, expanding beyond equities and mutual funds to include portfolio management services (PMS), commodities, bonds, and advisory. This move is explicitly aimed at reducing reliance on a single revenue stream amid tighter regulatory norms for derivatives trading.
2. Digital-Only Mutual Fund Strategy: The new joint venture JioBlackRock launched India’s debut of BlackRock’s Systematic Active Equities (SAE) framework. This quant investment unit utilizes AI and Machine Learning (ML) to analyze over 400 alternative data sources—such as social media posts, satellite imagery, and quick commerce deliveries—to extract insights, demonstrating a localized, tech-driven approach to investment management. JioBlackRock is pursuing a digital-only distribution approach to bypass traditional distributors, offering lower expense ratios as a key competitive tool.
3. Prediction Markets (Future Frontier): The convergence of India’s fintech stack (Aadhaar, UPI) and its booming retail-investor base offers a unique opportunity to pilot regulated information markets, known as prediction markets. The sources describe these as "derivatives of information" that use prices to aggregate dispersed knowledge and price non-financial risks like elections, policies, and climate milestones. Current ambiguity under the Public Gambling Act (1867) and the Securities Contracts (Regulation) Act (1956) constrains them, but suggestions were made for pilot programs in the GIFT City Sandbox using contracts tied to macroeconomic or policy outcomes.

III. Digital Consumer Services and Telecom Battleground

Digital-first consumer businesses continued their intense battle for market share through capital-intensive expansion and strategic shifts, while telecom operators leveraged AI to attract high-ARPU customers.

A. Quick Commerce (Q-Comm) and Capital Constraints

The quick commerce sector demonstrated high revenue growth but widening losses due to aggressive digital expansion.

• Swiggy’s Expansion Cost: Swiggy reported a Q2 FY26 net loss of ₹1,092 crore (up 74.4% y-o-y), primarily due to its aggressive Instamart quick commerce expansion. Instamart revenue doubled (102% y-o-y jump) to ₹1,038 crore.
• Capital Buffer: To maintain financial agility amid fierce competition, Swiggy is considering raising up to ₹10,000 crore through a QIP. Swiggy’s CEO cited the need for a strategic reserve as competition intensifies.

B. Telecom AI Supremacy

Telecom operators are moving beyond 5G competition to battle for "AI supremacy" to boost customer spending.

• Jio’s AI Offering: Reliance Intelligence, leveraging Google's 7.7% stake in Jio Platforms, announced it would offer Jio users the latest version of Google Gemini AI Pro free of cost for 18 months (valued at ₹35,000). This strategy is aimed at grabbing higher tariff-paying customers to boost Average Revenue Per User (Arpu).

C. Digital Infrastructure and Hardware

• Logistics Tech: Logistics and e-commerce enablement company Shiprocket narrowed its net loss and saw core business revenue grow by over 20% y-o-y, driven by domestic shipping and value-added tech offerings.
• Aviation AI: Adani Airport Holdings Limited (AAHL) announced a strategic deal with AIONOS to implement a multi-lingual omni-channel agentic AI solution to enhance the conventional passenger help desk experience and offer personalized support across Adani airports.
• Space/Internet Connectivity: Elon Musk-owned Starlink Satellite Communications began hiring for finance and accounting domains in India following approval to launch satellite internet services.

IV. Overcoming Indian Policy and Capital Constraints

Industry veterans debated that despite India having the necessary human capital and growing physical capital (data centers), the primary constraints for maximizing its tech ambition are financial capital (risk funding) and certain policy gaps.

• Capital Crunch: In the last decade (2014-2024), India attracted only $160 billion in startup funding, compared to $2.35 trillion in the US, with India remaining heavily dependent on international risk capital.
• Intellectual Property (IP) Drain: The lack of robust IP laws means that "code cannot be patented in India," which sometimes drives tech startups to move their headquarters overseas (e.g., to the US) for IP protection and funding, resulting in a potential "IP drain".
• The AI/Services Dilemma: The Indian tech landscape remains heavily 90–95% services-based. Transitioning to a new AI path requires massive capital injection into new companies, as incumbents are generally ill-suited to lead "tectonic shifts in technology".