Be Aware of These Risks to Your Portfolio

In the technology sector, the primary headwind is the erosion of pricing power driven by the rapid evolution of generative artificial intelligence (AI).

For decades, the Indian IT model thrived on the arbitrage of human effort, where revenue was a direct function of billable hours and headcount.

This effort-based pricing model is currently facing a deflationary shock.

As agentic AI models become capable of automating complex software engineering tasks, legacy code modernization, and routine maintenance, the value of the traditional junior engineer is being commoditized.

Global clients are increasingly demanding productivity gains be passed back to them in the form of lower contract values. This creates a scenario of revenue deflation where IT firms must do more work for the same or less money.

Unlike previous technological shifts like cloud or mobile, which created massive new service lines, the AI transition is initially cannibalistic.

It compresses the time and labour required for high-volume tasks before the new, high-value AI consulting revenue is large enough to bridge the gap.

Consequently, return on equity (RoE) and operating margins for IT heavyweights are likely to remain stagnant or decline in the near term, as the cost of investing in AI infrastructure and talent outweighs the immediate revenue benefits.

Simultaneously, the banking sector is grappling with its own version of a pricing squeeze, centered on the rising cost of liabilities.

While credit demand in the Indian economy remains robust, the era of easy, low-cost liquidity has vanished. Banks are currently locked in an intense competition for deposits to fund their aggressive loan growth.

This has led to a structural shift where the growth of deposits consistently trails the growth of credit, forcing banks to hike interest rates on term deposits and offer aggressive incentives to attract retail savings.

As interest costs on deposits rise, the net interest margins (NIMs) that define banking profitability are under severe pressure. The heavyweights, which previously benefited from a high share of low-cost current and savings accounts, are seeing customers migrate toward higher-yield alternatives.

This repricing of the liability side of the balance sheet (deposits and borrowings, which are costs) happens faster than the repricing of the asset side (loans and investments, which are revenue streams).

This leads to a period of compressed earnings growth. Such a scenario makes it difficult for the large banking stocks to justify their historical valuation premiums.

Looking ahead, the risks shift from pricing power to the stability of the underlying business models.

In the IT sector, the most significant threat is the potential loss of top-tier talent.

As the industry moves from a volume-based game to a value-based one, the demand for highly specialized skills in AI architecture, cybersecurity, and data science has skyrocketed.

However, the traditional IT giants are often viewed by elite talent as legacy environments with rigid hierarchies. There is a growing trend of the most capable engineers moving toward specialised startups, global capability centers, or even non-tech firms that are building their own internal AI stacks.

If the heavyweights lose their best minds to more agile competitors, their ability to execute the complex digital transformation projects of the future will be compromised.

This talent drain not only raises the cost of retention but also threatens the long-term competitive moat of these organizations, potentially turning them into zombie service providers that can maintain legacy systems but cannot lead the next wave of innovation.

On the banking front, the medium-term concern is a looming deterioration in asset quality, specifically within the retail and unsecured segments. After years of focusing on corporate deleveraging, Indian banks pivoted aggressively toward personal loans and gold loans to drive growth.

The loan concentration has created a massive exposure to the most sensitive segments of the consumer economy. Personal loans, often unsecured and marketed through digital channels with minimal friction, are susceptible to rising delinquency rates (NPAs). As the cost of living remains high and wage growth in white-collar sectors like IT slows down, NPAs could climb up.

Similarly, the surge in gold loans has exposed banks to the volatility of bullion prices and the risk of localized economic distress. If a correction in gold prices occurs or if the credit cycle for individual borrowers turns, the industry could see a sharp spike in NPAs.

Unlike corporate defaults, which are lumpy but often involve collateral and restructuring, a retail default cycle is granular and expensive to manage. This leads to higher provisioning requirements that could eat into capital buffers for years.

The structural risk to a portfolio heavily weighted in these two sectors is therefore two-fold.

One side is the immediate reality of stagnant returns as AI-led deflation hits IT and deposit costs hit banks.

The other side is the gathering storm of operational risks. Primarily the loss of human capital in IT and the potential for higher NPAs in banking.

When these sectors represent 30-40% percent of an index, their inability to grow earnings at historical rates acts as a massive drag on overall market performance.

Investors who are comfortable giving higher and higher allocation to these sectors must recognize that the environment of 2026 is fundamentally different from the previous decade.

The safety once associated with these sectors is being replaced by a complex set of structural challenges that suggest the path to outperformance may have several hurdles.

Diversifying away from this concentration is no longer just a matter of tactical positioning. It's a strategic necessity to protect your portfolio against the headwinds that could erode value in the traditional pillars of the Indian stock market.

Warm regards,


Tanushree Banerjee
Editor, StockSelect
Quantum Information Services Private Limited (Research Analyst)