AI stocks have been hogging the limelight for over a year now. Some artificial intelligence (AI) exchange-traded funds (ETFs) have surged over 100% over the last year, while stocks such as Micron Technology have soared nearly 900% since last year. Shares of chipmaker Intel Corporation have surged 565%, while those of NVIDIA have gained 45% in the last year.
This AI boom has driven tech-heavy Nasdaq 12% higher this year so far, while Korea’s Kospi has soared more than 90% year-to-date.
Taiwan’s share market has surged over 100% in the past year, as the country, as per reports, is the biggest producer of the chips that power AI technology.
There is little doubt that artificial intelligence (AI) will transform virtually every sector of the economy, giving it a long runway for growth. However, that does not mean investors’ enthusiasm for the technology cannot prove misplaced.
While the opportunity is real, experts warn that the AI trade may be running ahead of fundamentals, with parts of the market pricing in a near-perfect future.
Stock markets are never short of risks. At this juncture, investors may be more focused on major macroeconomic risks such as the Middle East conflict and crude oil price volatility, both of which could weigh on global economic growth, trigger tighter monetary policy, and usher in a prolonged period of market consolidation.
However, beyond these traditional risks of geopolitical tensions, trade disputes, and oil-price shocks, investors may be underestimating a major risk of excessive optimism about AI.
Is AI in a bubble?
Many experts find it difficult to answer this question in black and white. For some, the sector is too hot to sustain its gains, while several others say AI remains a long-term bet since the scope of its growth remains vast.
“AI is likely to be one of the defining technologies of this century. The question is not whether AI will create value. It will. The real question is whether investors are paying a reasonable price for that future. Great technologies create opportunities. Disciplined investing determines who benefits from them,” said Shruti Jain, Chief Strategy Officer, Arihant Capital Markets.
For investors, the current AI trade requires a shift from speculative hype to fundamental valuation.
As per Ravi Singh, Chief Research Officer at Master Capital Services, much of the initial market surge was driven by narrative and multiple expansion, rather than immediate cash flows. The risk lies in overlooking the high capital expenditure, chip shortages, and lengthy monetisation timelines that companies face.
Nirali Bhansali, an equity fund manager at SAMCO Mutual Fund, pointed out that the key risk today is not that AI will fail, but that valuations of some AI‑linked companies have raced ahead of earnings visibility.
According to Bhansali, any slowdown in AI spending, monetisation challenges, regulatory hurdles, or weaker‑than‑expected returns on vast infrastructure investments could spark corrections.
Bhansali suggests investors should avoid treating AI as a single thematic trade.
“Prioritise businesses with durable competitive advantages, predictable cash flows, and clear pathways to monetise AI rather than companies benefiting only from narrative-driven re-ratings. The next phase of the AI cycle will likely reward execution over excitement. Keep exposure to high‑quality AI beneficiaries, but limit concentration risk and valuation excesses,” said Bhansali.
Paresh Bhagat, the Chairman of Mangal Keshav Financial Services, has a similar view.
“Investors should differentiate between the long-term structural potential of this theme and the near-term valuations being assigned to companies associated with it. Markets often price in future growth well before the earnings actually materialise, and that creates the risk of periodic corrections even within a strong long-term trend,” said Bhagat.
Bhagat believes AI is still not in a bubble in the traditional sense, as enterprises globally continue to increase spending on the underlying infrastructure and capabilities driving this shift.
However, he added that not every company associated with the theme will necessarily emerge as a long-term winner. In several cases, stock prices have appreciated much faster than earnings growth, which increases valuation risk.
How should investors do AI trading?
Singh said investors should transition from broad AI themes to a selective, value-driven strategy.
“Focus on infrastructure providers (semiconductors, data centres, and power utilities) with robust cash flows, and pragmatic adopters- established enterprise software and services companies successfully integrating AI to expand margins, rather than speculative startups lacking a clear path to profitability,” said Singh.
As per Bhagat, one should focus less on companies merely carrying the narrative and more on businesses that are genuine beneficiaries of the underlying capital expenditure cycle.
“Investors should approach this trend with the same discipline they apply to any structural opportunity – focusing on earnings visibility, balance-sheet strength, execution capability and valuation. This is likely to remain a multi-year opportunity, but future returns will increasingly depend on earnings delivery rather than excitement around the theme alone,” said Bhagat.
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Disclaimer: This story is for educational purposes only and does not constitute investment advice. The views and recommendations expressed are those of individual analysts or broking firms, not Mint. We advise investors to consult with certified experts before making any investment decisions, as market conditions can change rapidly and circumstances may vary.
