Goodbye hero stock… …hello diversified chips, cloud and software AI investments?
Byline: Angela Tan Senior Business Correspondent
Goodbye hero stock… …hello diversified chips, cloud and software AI investme…
Goodbye hero stock… …hello diversified chips, cloud and software AI investments?
Opportunities broaden, as well as ways to build more balanced AI exposure, as the industry matures.
Angela Tan
Senior Business Correspondent
Artificial intelligence has become the defining investment theme in recent years, reshaping industries from healthcare to finance and opening new growth avenues.
Experts say one approach investors can consider is to build a basket of AI stocks across the value chain. For example, combining chip leaders (Nvidia, Broadcom, AMD, TSMC), cloud platforms (Microsoft, Amazon, Alphabet) and selected software names (Palantir, ServiceNow) to reduce single-stock risk.
Yet the market’s enthusiasm has not been without turbulence, as investors sift through companies that can harness the technology and those that cannot.
This was witnessed five weeks into 2026, when fears of AI-driven disruption triggered heavy selling in the software sector, wiping out US2.5 trillion) in valuations.
Concerns intensified following reports that Claude Cowork, an AI-powered productivity platform, could put traditional software vendors out of business. The S&P 500 software and services index tumbled 30 per cent in February from its October 2025 peak.
Selling pressure spread to other service-based industries seen as vulnerable to new AI tools. These include financial brokerages, data analytics, insurance, commercial real estate and wealth managers.
Despite reporting strong earnings, shares of software companies, including Microsoft, Adobe and Salesforce, tumbled.
As the lines between hype and reality become blurred, how can investors stay exposed to the long-term AI story without getting hurt by short-term volatility?
Is it a bubble, and is it popping?
The blanket sell-off fails to distinguish between vulnerable and resilient business models, experts say. It assumes a bear case that AI will let firms replace incumbent software easily and cheaply.
Analysts argue that incumbent software systems are complex and hard to replace. There are “integration complexities” and switching costs involved.
HSBC’s head of US technology research, Mr Stephen Bersey, says once a large platform application is installed and a customer’s business runs its critical operations on it, switching carries many risks.
If there is a disruption during a platform replacement, normal operations can stall, loyal customers can leave forever, brands are tarnished and revenue can hard-stop until the issues are resolved, he says.
Mr Ryan Hammond, portfolio strategist at Goldman Sachs Research, says the industry’s fundamentals are still strong.
The market is starting to see more industry-specific applications rolled out from large language models that are prompting investors to question the long-term sustainability of certain business models, he says. This scrutiny is contributing to greater divergence among technology stocks.
Investors like these companies’ earnings and growth over the next few years. However, they are unsure how strong the business will be further down the road. Given that a big chunk of a stock’s price comes from profits far in the future, even small doubts about long-term prospects can matter more than today’s solid numbers, he says.
AI-related spending to build data centres, buy chips and secure talent is also unnerving investors.
The Big Four hyperscalers – Microsoft, Alphabet, Amazon and Meta Platforms – have committed about US$650 billion to data centre capital spending in 2026, up nearly 60 per cent from 2025 levels. They are expected to require billions of dollars more to meet expected demand before the end of the decade.
Time and money will determine who will succeed, and when. US President Donald Trump’s administration has added a new layer of uncertainty for these companies, with his tariff announcements disrupting international trade.
For those looking to buy the Magnificent Seven tech stocks for exposure to AI, bear in mind that they now come with concentration risks on top of their high valuations.
Investors already hold very large positions in the Mag Seven tech stocks. This means most people who wanted to buy have already done so, leaving less new money or dry powder to push prices higher. Thus, some experts expect the Mag Seven to keep underperforming in the broader market.
As the industry matures, investors are gravitating towards companies that show fiscal discipline and progress in monetisation, says Mr Ritesh Ganeriwal, managing director and head of investment advisory at Syfe, a digital investment platform.
“2026 is likely to be less about who spends the most on AI and more about whether these companies can sustain their elevated earnings growth and meet Wall Street’s high expectations,” he says.
Coping with the mood swings of adolescence
The market behaviour is typical of a later-stage bull market, says Mr Jay Woods, chief market strategist at Freedom Capital Markets.
The market may find it harder to push significantly higher, but that does not necessarily mean the bull market is over.
Investors should not cling to yesterday’s winners. Instead, they should reposition into the areas now taking the lead, he says.
Big tech firms remain central to the AI boom. Chipmakers like Nvidia and Taiwan Semiconductor Manufacturing Co (TSMC) supply the hardware powering AI, while cloud companies such as Microsoft and Amazon integrate it into their services.
Rising demand for AI infrastructure – from chips to memory and wafers – is supporting profits across the supply chain, with equipment makers benefiting as chip foundries ramp up spending to expand capacity.
Second-tier beneficiaries are emerging – from workflow software providers like ServiceNow and data platforms such as Palantir, to social and ad platforms like Meta – that use AI to improve targeting and engagement.
For Singapore investors, this broadening stack means AI exposure can be diversified across chips, cloud and software, rather than concentrated in one hero stock.
Investors should diversify across industries, geographies and asset classes to counter concentration risk, US dollar headwinds from geopolitics and rate cuts, Mr Ganeriwal says.
Mr Afdhal Rahman, executive director of wealth advisory at OCBC, said investors should consider seeking opportunities in sectors that are relatively insulated from AI disruption risks.
This includes cyclical US sub-sectors such as capital goods, materials and energy, which have delivered robust returns year-to-date.
Sectors like materials remain beneficiaries of persistent geopolitical tensions and the race for resources, as the sector is generally home to producers or miners of critical minerals and precious metals.
Beyond the US, emerging markets stand to gain from dollar depreciation, Mr Ganeriwal says.
Emerging market stocks jumped about 34 per cent in 2025, nearly double the 18 per cent gain in US equities, helped in particular by China’s policy stimulus and progress in AI-related sectors.
Developed markets beyond the US also performed strongly, led by European banks, Japan and Britain’s most highly capitalised blue chips listed on the London Stock Exchange represented by the FTSE 100 index.
European banks benefited from healthy net interest margins, solid capital buffers and a still-resilient economic backdrop.
Japan gained from finally shaking off deflation and pushing reforms to boost shareholder returns, such as higher dividends and buybacks.
The FTSE 100, where around four-fifths of large-cap revenues come from overseas, effectively acted as a proxy for global growth rather than just the British economy.
By asset class, gold was the standout asset in 2025, with sharp gains driven by geopolitical tensions, heavy central bank buying, strong exchange-traded fund inflows and a weaker dollar, underscoring its role in diversified portfolios. These supports are still largely in place in 2026 despite the latest pullback, Syfe’s Mr Ganeriwal says.
Bonds also had their best year in 2025 since 2020 as inflation eased and yields remained historically high. With policy rates still above estimates of neutral, markets expect further cuts from the US Federal Reserve in 2026, giving bonds room for additional capital gains as yields move lower, he adds.
All this means Singapore investors no longer need to punt the next Nvidia to gain exposure to AI.
As the industry shifts from hype to infrastructure and everyday adoption, the investable universe is widening, and so are the ways to build more balanced AI exposure.
Policy tailwinds closer to home
Investors may want to start paying more attention to Asia’s often-overlooked role in the AI ecosystem, especially its leadership in chip manufacturing, says Mr Afdhal.
The expansion of data centres across ASEAN could open up opportunities in related sectors like property, energy, cooling systems and IT services.
Singapore’s push to become a regional AI hub is also gathering momentum, with leading companies building out infrastructure and expanding AI adoption across sectors.
Singtel has been identified as a top AI enabler, thanks to its aggressive data centre expansion in Singapore and partnerships supporting Nvidia’s accelerated AI factories in South-east Asia.
Asset manager and operator Keppel also stands out as a likely beneficiary given its expertise in integrated solutions that combine power, connectivity, data centres and decarbonisation.
Similarly, Sembcorp Industries is well-positioned to capture gains through its power and natural gas operations.
In terms of AI adopters, Grab is recognised as a major driver of AI innovation in Asean while leading in areas such as autonomous mobility.
Sea, Singapore Airlines and ST Engineering have also emerged as key players in the AI space. ST Engineering is rolling out AI-driven solutions across defence, aerospace and smart-city projects, aiming to more than double its digital revenue to $1.3 billion by 2029.
Experts say one approach investors can consider is to build a basket of AI stocks across the value chain. For example, combining chip leaders (Nvidia, Broadcom, AMD, TSMC), cloud platforms (Microsoft, Amazon, Alphabet) and selected software names (Palantir, ServiceNow) to reduce single-stock risk.
Those who prefer instant diversification can look at broad tech or AI-themed exchange-traded funds.
Doing so, you may enjoy the AI ride without having to worry about the occasional bump.