Are 'Old Economy' Stocks The Real AI Winners? Goldman Flags A Major Market Shift

For most of the period following the 2008–09 financial crisis, markets repeated the same mantra: own growth, own tech, ignore the rest.

Capital-light business models dominated. Software scaled. Margins expanded.

With interest rates pinned near zero and liquidity abundant, the longest-duration assets — particularly mega-cap technology stocks — delivered outsized returns.

Meanwhile, capital-heavy sectors tied to physical assets languished, often dismissed as "value traps."

But according to a new research note from Goldman Sachs equity analyst Peter Oppenheimer, that narrative may be undergoing a structural shift.

Are so-called ‘old economy’ stocks quietly emerging as the next AI trade?

AI Spending Is Reconnecting The Physical And Digital Worlds

Hyperscalers – which include tech behemoths such as Amazon.com Inc., Meta Platforms Inc., Alphabet Inc. – have unleashed massive capital expenditure to build data centers and computing power. That spending does not stop at silicon.

It spills into utilities, power grids, industrial equipment and construction.

Many of these sectors have been starved of capital since 2008. Overcapacity and low returns crushed investment in traditional industries dominated by low-multiple value stocks.

Now, that drought is ending.

“Investment in AI infrastructure coupled with the renewed boost in defense spending are re-igniting returns on investment in many of the physical assets that had long lagged behind, just as investors fear the slowing of returns from record high levels in the technology space,” Oppenheimer said on Thursday.

For the first time since the commercialization of the internet roughly 25 years ago, future technology growth prospects are increasingly dependent on physical infrastructure: data centers, semiconductor fabrication plants, power grids and energy supply.

AI is not just software. It is energy-intensive, capital-intensive and infrastructure-heavy.

Are Magnificent 7 Returns Peaking?

At the same time, investors are questioning whether Big Tech can justify its enormous AI outlays.

“The surge in AI capex by the hyperscalers has prompted investors to question their ability to collectively generate adequate returns on investment, prompting the pace of performance to slow, and the dispersion of returns within the technology sector to widen,”

Performance has already cooled.

The Magnificent 7 delivered a 75% return in 2023, the year after ChatGPT launched. Gains slowed to about 50% in 2024. In 2025, returns have slipped below 25%.

The era of uniform mega-cap dominance appears to be fading.

Value Traps Or Value Creators?

Since early 2025, market leadership has shifted.

Gold, emerging markets, Japan's Topix, industrial metals and Value stocks have outperformed. Over the past three months, the iShares Russell 1000 Value ETF has outperformed the iShares Russell 1000 Growth ETF by 18 percentage points.

That marks a sharp break from the prior decade.

Oppenheimer says the opportunity set is shifting, as "value parts of the market that have long been neglected as ‘value traps'" could evolve into "value creators" by boosting cash flows and returning more capital to shareholders through dividends and buybacks.

Goldman maintains that equities are likely to remain the best-performing asset class. However, the drivers of returns are broadening.

What This Means For Investors

The AI revolution is not just about chips and software anymore. It is about power plants, transmission lines and industrial capacity.

For investors accustomed to chasing the next AI software winner, the next leg of the AI trade may look very different. It may run through power grids, industrial metals and factories, not just code.

Rather than relying on a narrow group of mega-cap growth stocks, investors may find more opportunities across sectors tied to physical assets and real investment cycles.

This dispersion is creating new chances to generate alpha, or excess returns versus the market.

If Goldman is right, the real AI winners may not sit only in Silicon Valley.

Image: Shutterstock