Big Tech's giant headache: billions in AI capital spending and investors demanding quick results

By Marta Norton

Implementing AI carries plenty of risks - most of which stem from its tremendous potential

For investors looking for instant gratification from AI stocks, frustration may lie ahead

With the promise of productivity gains across the economy in record time, companies at the center of AI infrastructure - hyperscalers and chip designers - have raced to invest, turning to debt and circular financing in their haste to build out the AI supply chain.

At first, investors loved it. Maybe a bit too much. Last fall, valuations bubbled among the "Magnificent Seven" stocks and others at the center of the AI trade, with little regard to the consequences of such reckless spending or the uncertain path to monetization.

And then - as often happens in markets - investor sentiment flipped.

Fear about these stocks eclipsed enthusiasm, and despite continued earnings strength in fourth-quarter earnings, the stocks most closely associated with AI suffered.

Is the skepticism warranted? For investors wanting instant gratification from AI stocks, frustration may lie ahead. The investment horizon for these companies requires patience - and for a long-term investor, patience may spell opportunity.

The earnings test

Over the past few years, technology companies have carried the broader U.S. market's earnings growth, meeting or exceeding double-digit expectations. Now that's no longer enough. Investors are looking for tangible signs of AI monetization - signals that companies are putting AI to work in their business models and improving revenue and profit margins as a result.

The benefits of AI are likely to accrue unevenly and over time. Some companies may realize gains sooner. For much of the market, and especially the big-spending hyperscalers, the costs - investment, integration, disruption - arrive before the payoff.

As a result, the next earnings season could again fail to ignite investor enthusiasm for AI's "A-list" companies.

Productivity bottlenecks

Another overarching question for the AI trade is what stands in the way of future productivity? If AI drives meaningful efficiency gains, it can fuel stronger growth, bigger margins and a more resilient economy. That's the bull case - and it's not unreasonable.

But as with any massive capital-spending wave, there are bound to be bottlenecks. In the dot-com era, it was fiber optics, storage and servers. This time around, it's GPUs and gigawatts. Even basic construction labor, cement, rebar and cooling systems could pose constraints. For each bottleneck we can imagine or anticipate, there are a dozen others we can't. These bottlenecks put distance between today's cost and tomorrow's reward, creating another potential reason for AI's valuation stagnation.

The opportunity is real. But so is the likelihood that the path from here to there is uneven - and that markets may need to recalibrate along the way.

Today's leaders may not be tomorrow's winners

AI hasn't yet made it clear which companies will be winners. Consider how many names from the dot-com era are history now. Names such as Netscape, WorldCom, JDS Uniphase and EMC.

In this environment, investors need to be selective and prioritize several important factors:

1. Diversification isn't a formality: Since no one knows the winners across the AI ecosystem, your AI exposure should be broad, rather than centered on one or two hotshots.

2. Quality matters: Companies with strong cash flow, manageable leverage and pricing power are typically better positioned to navigate uneven growth and higher capital costs.

3. Be disciplined about what you pay for growth: It's easy to get caught up in the hype when all anyone can see is potential growth. But in a long race like AI, we should expect moments of doubt. Waiting for periodic disappointments creates buying opportunities.

4. Watch what is changing - not just what is working: Market leadership, earnings revisions, credit conditions and supply bottlenecks can shift at the margins. Those shifts often matter more than the dominant narrative.

AI is a meaningful development with profound societal and economic implications. Shifting leadership, uneven sentiment and potential bottlenecks are part of AI's maturation process. To succeed with these investments, shareholders will need a lot of patience and prudence.

Marta Norton is chief investment strategist at financial services firm Empower.

More: AI spending will boost productivity - but first it'll make even the most efficient firms look like slackers

Plus: Why 'Rule of 10' stocks like Nvidia and Meta are now poised for a comeback, according to Goldman Sachs

-Marta Norton

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04-18-26 1543ET