AI disruption sparks Halo trade as investors flee software for heavy assets and infrastructure

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A new investment strategy called Halo—Heavy Assets, Low Obsolescence—is gaining traction as AI fears pummel software stocks. The S&P Software Index dropped 20% this month while mining stocks surged over 100%. Goldman Sachs argues this marks the end of a 15-year era favoring capital-light business models, as investors seek AI-proof companies with physical infrastructure that's difficult to replicate.

AI Scare Trade Reshapes Investment Strategy

A dramatic market shift is underway as AI anxieties trigger what Josh Brown, CEO of Ritholtz Wealth Management, has termed the Halo trade—an acronym for Heavy Assets, Low Obsolescence

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. This counter-movement to the AI scare trade reflects growing investor concern about which businesses can maintain relevance as artificial intelligence disrupts traditional business models. The S&P Software Index has plummeted roughly 20% this month alone, while sectors once considered stagnant are experiencing remarkable revivals

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. The carnage extends beyond software, with real estate, IT, cybersecurity, and insurance all experiencing similar freak-outs. IBM dropped 13% after Anthropic demonstrated how Claude can modernize legacy code, while DoorDash fell 6.6% merely from appearing in a viral doomsday AI scenario

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Source: Axios

Source: Axios

Goldman Sachs Identifies Dual Shock from AI

Goldman Sachs strategists Guillaume Jaisson and Peter Oppenheimer have identified what they describe as a dual shock transforming global equity markets

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. The first disruption targets the Software-as-a-Service (SaaS) business model directly. "AI is disrupting many of the traditional new-economy business models that dominated the past decade," Jaisson noted

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. The recent selloff doesn't reflect an earnings collapse but rather a repricing of terminal value and long-term margin durability. The second effect proves equally transformative: AI is converting former capital-light champions into capital-intensive giants. U.S. hyperscalers are deploying approximately $1.5 trillion in capex between 2023 and 2026—compared to roughly $600 billion across their entire history before 2022

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. In 2026 alone, their capital expenditure cycle is projected to exceed $650 billion.

Source: Benzinga

Source: Benzinga

Physical Assets Trump Digital Scalability

AI-proof businesses share two defining characteristics according to Goldman Sachs: they rely on substantial physical capital with high barriers to replication, and they own assets whose economic relevance persists across technological cycles

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. Examples include transmission grids, pipelines, utilities, transport infrastructure, critical machinery, and long-cycle industrial capacity. These operations prove difficult to replicate due to cost, regulation, engineering complexity, or construction timelines. The data validates this narrative: the S&P Global Mining Index has surged over 100% from last year, while Budweiser stock—previously written off after its controversial marketing misstep—has climbed 48%

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. Brown's go-to example contrasts Delta Air Lines with Expedia. Until this year, both stocks moved in tandem with the travel sector. Now they've decoupled dramatically: Expedia, vulnerable to replacement by AI chatbots, is down 6% from last year, while Delta has gained 8.3%

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End of Capital-Light Growth Era

For 15 years, investors favored asset-light business models—software companies without significant labor or infrastructure that generated recurring revenue through subscriptions

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. "We reached a point where people were saying, 'what else would I want to invest in?'" Brown explains. "That era just came to end."

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Old market paradigms—growth versus value, defensive versus cyclical—no longer apply. "That's not what's going on now," Brown tells Axios. "Throw all that out." The new metric centers on a single question: disruptable or not?

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Investment banks are embracing this framework. Goldman Sachs launched SPXXAI, a new index allowing investment in the S&P 500 benchmark minus all AI-related holdings

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Company Resilience Against AI Remains Uncertain

The challenge for investors lies in distinguishing temporary panic from permanent obsolescence. Some battered stocks may be absurdly cheap; others will never recover. "We don't yet know which is which or what the timetable might be," Brown wrote

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. The situation mirrors the dot-com bubble burst when investors fled tech stocks en masse, unable to differentiate between Pets.com and Amazon. Goldman Sachs identifies utilities, basic resources, energy, and telecom as unmistakably capital-intensive sectors built on regulated infrastructure, high fixed investment, and long-lived assets with limited obsolescence

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. At the opposite extreme, software and IT services, internet, media, and digital platform businesses fall squarely into the capital-light category. If AI compresses margins in software while driving massive physical investment elsewhere, the next market winners may not be the most scalable—they may be the hardest to replace

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. With no clear endpoint to the scare trade in sight, investors face an extended period of uncertainty about which companies can demonstrate genuine company resilience against AI disruption

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