Market sentiment toward artificial intelligence (AI) is currently mixed. While it was the premier sector to invest in during 2023 through 2025, investors are a bit more selective and skeptical in 2026. They see the AI hyperscalers spending record-setting amounts on capital improvements, yet returns on this spending are still to come (if they come at all).
Investors considering AI stocks need to be patient. The reality is, most companies haven’t started using AI on a day-to-day basis. Once they do, they’re going to need a lot more computing capacity than is available right now. Those who are bullish on the AI trend should look at this short-term skepticism as a long-term AI buying opportunity.
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AI usage is rapidly growing, but there’s still a large majority of the population that isn’t using it. Businesses are even worse, and according to research done by The Motley Fool, only 18% of businesses are currently using AI. That figure is expected to rise to 22% in the next few months, showing rapid adoption. But businesses are still a long way away from an AI-first approach that we keep hearing about.
Larger firms are a bit more tech savvy and have a 27% usage rate, but that’s still way under half. There is clearly more room to use AI. AI computing resources are still constrained right now, even with relatively minor usage among the business community. As a result, there is still a huge investment opportunity in AI.
We’re going to need a lot more infrastructure, and that brings to mind three stock picks that could thrive.
By 2030, McKinsey & Company projects that about $7 trillion in data center capital expenditures will be needed to meet AI computing demand. For reference, the AI hyperscalers are expected to spend about $650 billion this year, so there’s still a long way to go to meet the threshold necessary to achieve this goal.
Two companies that will thrive from continued build-out are Nvidia (NASDAQ: NVDA) and Taiwan Semiconductor Manufacturing (NYSE: TSM). Nvidia makes graphics processing units (GPUs), which have become the go-to computing unit of choice for facilitating AI workflows. While there are alternatives out there, none have the full-stack capabilities that Nvidia’s GPUs have and the ability to move workloads from provider to provider. An investment in Nvidia is a bet that more GPUs are needed to process all of the AI workload yet to come online — a pretty safe bet.
