Stocks profiting from the AI infrastructure spending boom have been powering market returns thus far in 2026, providing a tailwind to makers of memory chips, storage hardware, and AI servers—key components of the massive data-centers build-out.
But at some point, the market’s attention may shift to companies that can use AI in day-to-day operations—whether to boost productivity or to develop new products and services that are scarcely imaginable today.
The health care industry
One of the potential beneficiaries of this shift may be health care, an industry with a long history of innovation.
“I believe the implications of AI for the health care economy are going to be profound,” says Eddie Yoon, manager of Fidelity® Select Health Care Portfolio (
For investors, it may still seem early to position for this shift, as many of these possibilities are only beginning to take shape. But with valuations discounted after years of underperformance, health care might offer a surprisingly overlooked way to invest in AI's future potential.
The overlooked, yet vital, health care sector
Health care has lagged the broader market for years.
Investor sentiment has played a contributing role—in recent years investors have strongly favored stocks directly related to tech and AI. But there have also been meaningful fundamental issues. For example, a faster-than-expected rebound in the use of health care services after COVID weighed on insurer profitability from 2023 to 2025, while changes in reimbursement and coding dynamics also pushed up costs. Reduced government payment rates to private insurers participating in Medicare Advantage posed another challenge during this period.
This bout of underperformance has recently left the sector trading at a steep discount to both the overall market and to the industry’s historic average valuation of the past few decades. Yet many of these and other headwinds have been easing. For example, uncertainty around drug pricing eased in late 2025 when major pharmaceutical companies signed agreements with the government to lower drug prices.
Meanwhile, the health care sector is as important as it’s ever been to the US economy, and poised to grow even more relevant over time. At nearly 20% of GDP, the health care industry is not only enormous but also likely to benefit from a potent demographic tailwind.1 Nearly 20% of Americans are now 65 or older—a number rising each year. Medical spending per capita for those age 65 to 84 is 4 times that of people from 19 to 44 and nearly double that of those age 45 to 64.2
Phases of innovation for the health care sector
Yoon, who has managed Fidelity® Select Health Care Portfolio since 2008, believes AI advancement could unfold over several distinct phases. That potential could take many forms—from earlier disease detection using simple blood tests to breakthroughs in how new treatments are discovered and tested.
Phase 1
The first phase, he believes, could see AI help boost efficiency—for example, helping to reduce health-care-related administrative spending. The potential opportunity for savings is significant, given that administrative spending accounts for some $1 trillion a year, or about 20% of all spending on health care in the US.3
Phase 2
In the next phase, as AI computing power becomes more readily available, it could breathe new life into the industry’s research capabilities, leading to new drug discovery models. Here, Yoon draws an analogy with the late 1990s to early 2000s, when the first tech boom enabled breakthroughs such as the sequencing of the human genome, providing a powerful boost to downstream industries like biotechnology.
Phase 3
In the longest-term phase, Yoon envisions that AI could one day herald advances in the understanding of human biology, in a way that permanently accelerates the pace of further discoveries. As an analogy, Yoon points to physics and architecture. When a city wants to build a new bridge, it doesn’t need to run tests or experiments on how to build that bridge (in the way a drug company must with a drug trial). Because human beings have unlocked the first principles of physics, we know what it takes to build a sturdy bridge.
“We do not yet have those first principles of human biology,” Yoon says. But with advances he already sees in the industry, plus the potentially growing computing power of AI, he believes these kinds of innovative breakthroughs could one day become reality.
Fund top holdings4
Top 10 holdings of the Fidelity® Select Health Care Portfolio (
- 8.03% – Eli Lilly & Co. (
) - 6.89% – Danaher Corp. (
) - 4.91% – Johnson & Johnson (
) - 4.33% – Thermo Fisher Scientific Inc. (
) - 3.49% – UnitedHealth Group Inc. (
) - 2.40% – Alnylam Pharmaceuticals Inc. (
) - 2.21% – Gilead Sciences Inc. (
) - 2.17% – Boston Scientific Corp. (
) - 2.17% – Ascendis Pharma AS (
) - 2.03% – Abbvie Inc. (
)
(See the most recent fund information.)
When may AI start impacting the health care sector?
How long it may take for these potential advances to come to life may depend on how smoothly the present AI infrastructure build-out unfolds—and how long it takes for AI computing power to become more broadly available (and to fall in price).
While the timing of any breakthroughs remains uncertain, Yoon has been leaning into areas he believes could ultimately have exposure to these AI-related themes—but that could also benefit from more near-term tailwinds. For example, the fund has recently held overweights in subsectors such as life sciences tools and biotechnology, areas he perceives to be particularly dynamic.
Life sciences tools
Yoon believes that life sciences tools—the equipment, testing technologies, and analytics that underpin modern biomedical research—could benefit from the trend of manufacturing reshoring, which has been encouraged by certain federal policies. Yoon expects a capital investment wave as these facilities open over the next few years, which could stimulate rising demand for analytical tools.
“I believe that AI could drive efficiency in the clinical development part of R&D,” he says (referring to research and development). Clinical development accounts for the bulk of spending in pharmaceutical companies’ R&D budgets. So improvements in clinical-development efficiency could imply that “dollars may be reallocated to the 'R' side of things, which could be great for some life-science tool companies.”
Two large life science and diagnostics players in the industry that Yoon’s fund has held exposure to are Danaher (
Biotechnology
Yoon is also constructive on biotechnology for several reasons. For one thing, he says, the “hit rate” for clinical trials—meaning, the percentage of treatment candidates that are successfully able to move from one phase of trials to the next—has jumped dramatically in the past year or so.
“The quality of clinical data that I’m seeing out of the biotechnology industry has been unbelievable over the last 12 to 18 months,” Yoon says. “Biotech has been seeing a positive rate of change in innovation even though the AI tailwind hasn’t hit the industry yet.”
The industry has really come of age, he notes, with dozens of biotech companies generating $500 million or more a year of revenue. The industry’s economics are unusual: A biotech company can be unprofitable for a decade while it’s investing in new drug research, but once treatments are commercialized, these firms can suddenly become highly profitable. “The market consistently underestimates how once these companies turn profitable, they can become massively profitable,” Yoon says.
He’s held some biotech names for more than a decade, such as Alnylam Pharmaceutical (
Some of the treatments, improved life science tools and diagnostics, and research breakthroughs that Yoon anticipates being enabled by AI in the coming years may sound like science fiction today. That’s nothing new in the industry. Notes Yoon, “Within health care, innovation has been a constant and always underappreciated over my 25 years in the industry.”