Investing Through an Uneasy Boom

Welcome to Thoughts on the Market. I’m Erin Wright, Morgan Stanley’s U.S. Healthcare Services Analyst.

Today – the emergence of the self-directed patient and its implications.

It’s Tuesday, May 12th at 10am in New York.

A blood test ordered from your phone. A wearable that tracks your sleep or nudges you to move, recover, hydrate, or rethink last night’s dinner. Preventive health is moving out of the clinic and into everyday life. And that shift is becoming an investable theme.

In essence, healthcare is moving from reactive to proactive. Instead of waiting for symptoms, more consumers are using lab tests, wearables, imaging, and digital tools to spot some these risks earlier. And this shift reaches well beyond healthcare.

On our estimates, the U.S. spends about [$]3.4 trillion annually on chronic diseases, including lost economic productivity. About [$]1.4 trillion of 2024 spend was tied to preventable disease. So the big investment question is: can earlier detection and behavior change bend the cost curve?

We think expanded preventive testing, screening, and monitoring can help avoid roughly [$]200 billion to [$]800 billion of U.S. healthcare spend by 2050. That assumes preventive testing reduces preventable disease costs by about 10% to 30% based on our analysis.

Direct-to-consumer lab testing lets people order lab tests directly, often online, without starting with a traditional doctor visit. We see this as a roughly $4 billion U.S. market, which has more than doubled since 2021. And it’s no longer niche. Our AlphaWise survey found that about 34% of respondents completed a voluntary wellness lab test in the past three years. Among users, the average was 3.2 tests, suggesting this is not just a one-time behavior. The most common test was a general health profile, used by about 45 percent of recent testers.

Wearables are the other part of the story. Our survey found that 41 percent of respondents currently use a wearable or fitness device, while another 22 percent are interested in getting one. More importantly, people are acting on the data. 34 percent of wearable users today regularly change behaviors or decisions based on their device,  and 52 percent even sometimes do so, based on our survey.

That creates a feedback loop. A wearable might flag poor sleep. A lab test might show elevated glucose. A digital health tool might suggest changes to diet or exercise, or follow-up care. Over time, prevention starts to feel less like an annual event and more like a daily habit.

The sector implications are broad. In healthcare, more testing may initially actually increase utilization as people follow up on results. But over time, earlier detection could obviously support lower-cost of care and better chronic disease management. That also aligns with value-based care, where providers and payers are rewarded for better outcomes and lower total costs, not just simply more services.

In consumer sectors, better health tracking could shape food choices, reduce demand for some indulgent categories, and support products tied to hydration, lower sugar, protein, and functional benefits. Fitness may also benefit as gyms evolve from just workout destinations into broader wellness platforms, with recovery and coaching, and preventive health services layered in. Imaging is another emerging area, as screening shifts from reactive diagnostics toward earlier disease detection.

Of course, there is some risk that these health tracking and consumer-driven diagnostics trends could still prove to be a wellness craze rather than the new normal. Out-of-pocket costs, privacy concerns, inconsistent interpretations, and limited repeat testing are all real issues. But consumers are clearly taking more control of their health and increasingly asking, “What can I learn before I get sick?”

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Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley.

Today, a uniquely price insensitive development.

It's Monday, May 11th at 2pm in London.

Elasticity is one of the first concepts that they teach in economics, and for good reason.

It's the idea that our sensitivity to the price of something differs from item to item. If the price of pizza goes up, for example, you may decide to go out for burgers.

But if the price for something essential, like electricity, or deeply desired, like tickets to see your favorite artist perform; well, if those go up a lot, you're probably going to complain, but also end up paying anyway.

This latter category is what we would call inelastic. The demand for these items holds up even as the price increases, and maybe if the price increases quite a bit. And that is becoming very relevant as we all debate the AI build-out.

It's not an exaggeration that the investment in AI, chips, power, and datacenters is at the center of many market conversations. It's supporting U.S. growth despite a sharp slowdown in job creation. It's supporting stock market earnings, even as uncertainty over the Iran conflict continues to percolate.

Part of this importance is just the sheer size of this build-out. We estimate about $800 billion of investment by large U.S. technology companies this year, almost double their spending last year and triple their spending in 2024. But it's not just the size, it's the idea that this investment may happen almost whatever the cost.

Specifically, we're looking at a desire by multiple large companies to build out large AI infrastructure all at the same time, and that's increased the price of these components. The copper needed to wire together that data center? Well, it's up about 40 percent in the last year. A gas turbine to power it? Up 50 percent. The memory to run it? It's up 150 to 300 percent over the last year alone. And yet, despite these extremely large price increases, the demand to build in AI has been accelerating.

Our forecasts for 2026 spending have been consistently revised higher. And that $800 billion that we think is spent this year is set to be dwarfed by $1.1 trillion of estimated spending in 2027, based on the view of my Morgan Stanley colleagues.

This idea of inelasticity or price insensitivity extends even to the costs of financing the spending. Debt costs for these companies have increased this year, and yet they continue to issue at a record pace.

A quick aside as to why all this spending may be price insensitive or inelastic. AI is seen by these companies as, without exaggeration, maybe the most important technology in a decade. These companies have financial resources and the patience to wait it out, and they see gains to those who can figure out AI technology, even if the winner is not yet clear.

The inelastic nature of the AI theme is a classic good news, bad news story. To the positive, it suggests real commitment to this technology and that spending won't easily be shaken by outside events. That should help buttress overall growth and should also support earnings this year – a core view of Mike Wilson and our U.S. equity strategy team.

But there are also risks. It remains to be seen what returns can be generated from all of this historic investment. Robust demand for items, even as their price goes up, may cause those prices to increase even further. That's inflation happening at a time when core inflation measures are already well above the Federal Reserve's target. And if companies are less sensitive to the cost of their borrowing to fund AI, well, other companies could find their cost dragged wider in sympathy.

We continue to expect record supply and modest widening in the U.S. corporate bond market.

Thank you, as always, for your time. If you find Thoughts on the Market useful, let us know by leaving a review wherever you listen. And tell a friend or colleague about us today.