Key Points:
- Bank of America highlighted hidden artificial intelligence winners in the unloved energy and materials sectors.
- While S&P 500 semiconductors and tech hardware soared roughly 69% and 65% year-to-date, their valuations are now highly stretched.
- Long-only portfolio managers remain heavily underweight on these alternative energy (31%) and materials (6%) sectors.
- The brokerage pointed to quieter AI-benefit industries like workflow automation and low back-office intensity as less crowded value plays.
The massive, multi-trillion-dollar capital migration out of high-flying technology stocks is forcing Wall Street to aggressively search for hidden value beyond the highly crowded semiconductor and megacap sectors. A major research update from Bank of America has spotlighted a new class of artificial intelligence winners emerging within the unloved energy and materials sectors. While the “Magnificent Seven” and chip manufacturers have captured the lion’s share of the AI investment boom, the real-world operational demands of the technology are quietly driving massive, positive earnings revisions for the industrial infrastructure companies that power and supply these advanced digital networks.
This strategic shift arrives as the highly concentrated technology trade faces its first major correction of the year. A spectacular, months-long rally in AI hardware originally helped U.S. stock indexes shake off intense geopolitical conflicts in the Middle East to climb to historic record highs. However, a sharp bout of profit-taking recently took hold of the market as investors began to worry about stretched valuations, high price-to-earnings multiples, and fears that the AI trade has flown too high and too fast. This growing anxiety has left investors looking for a second degree of separation from the direct beneficiaries of the tech boom.
The scale of the price stretch in the direct technology sector is unprecedented, leaving very little room for further short-term multiple expansion. Year-to-date, the semiconductor and tech hardware segments of the S&P 500 have surged by approximately 69% and 65%, respectively, driving their valuation multiples well above historical averages. Even with the recent technical pullbacks, the Philadelphia Semiconductor Index—a primary barometer for global chip equities—remains up a whopping 64.8% for the year, proving that the traditional hardware trade is heavily oversubscribed and vulnerable to further profit-taking.
Instead of continuing to chase these expensive technology multiples, the investment bank recommends looking at the critical, physical infrastructure providers that make computing possible. These “AI capacity suppliers” fall squarely within the energy and materials sectors, yet their stock prices remain largely untouched by the speculative frenzy. While tech giants require an almost unimaginable amount of electricity, copper, and specialized physical components to construct gigawatt-scale data center networks, the companies supplying these raw resources are trading at highly discounted valuations compared to the software and chip sectors.
The commercial opportunity in these commodity sectors is particularly lucrative because institutional investors remain heavily under-allocated to them. Institutional portfolio managers are currently underweighting the energy sector by a massive 31% over the past three months, while underweighting the materials sector by 6%. This lack of institutional crowding means that these easy-to-miss infrastructure providers are trading at highly discounted multiples, offering an attractive and secure margin of safety for value-oriented portfolios looking to diversify away from high-beta tech exposure.
Investing in these material and energy sectors also provides a powerful macroeconomic shield against persistent global inflation. While recent data showed U.S. consumer prices cooling by 0.4% in June, the ongoing military conflict in the Middle East has pushed crude oil prices back near $85 a barrel, keeping the threat of energy-driven inflation highly active. In an environment defined by sticky inflation and negative real cash yields, companies that generate solid, inflation-protected income stand out as highly resilient, defensive hedges that can easily pass rising input costs directly onto their corporate customers.
The search for alternative AI value also extends to industries experiencing quieter, more practical productivity gains rather than massive capital expenditure cycles. The research note highlights companies focused on workflow automation, faster product development cycles, and low back-office labor intensity as prime candidates for long-term growth. Because these software-driven businesses utilize artificial intelligence internally to automate routine administrative tasks and streamline operations, they can achieve significant margin expansion without incurring the astronomical hardware costs associated with training frontier models.
The physical power demands of the AI data center buildout are also driving an unprecedented structural renaissance across next-generation energy providers. As traditional public utility grids struggle to meet the massive, multi-gigawatt electricity requirements of high-performance server farms, tech giants are increasingly bypassing public networks entirely. Companies are partnering directly with advanced nuclear energy developers to secure dedicated power. This trend was recently highlighted by the New York Stock Exchange debut of Standard Nuclear, which specializes in manufacturing advanced TRISO fuel to power small modular reactors co-located next to hyperscale data centers.
At the same time, the software layer of the AI economy is transitioning away from a highly consolidated, expensive model monopoly toward a more competitive and cost-effective landscape. To reduce their dependence on expensive, third-party closed APIs, enterprise clients are aggressively restructuring their software stacks to run on smaller, highly customized, open-weight models. This trend is visible in Microsoft’s recent decision to replace third-party OpenAI and Anthropic models with its own proprietary “MAI” models inside Excel and Outlook, reducing computational expenses and driving higher margins for its workplace assistant.
Ultimately, the transition of capital away from semiconductor giants to these alternative non-tech sectors demonstrates that the global AI boom is entering a mature, infrastructure-led phase. By focusing on underloved energy and materials suppliers alongside quieter workflow automation plays, investors can successfully capture the massive economics of the digital transition without exposing themselves to the extreme volatility of the tech sector. As the critical second-quarter corporate reporting window continues to unfold, the companies capable of delivering clean, inflation-protected cash flows will emerge as the true, sustainable winners of the artificial intelligence era.
