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The third quarter just wrapped, and the pure AI trade of Nvidia (NVDA) and its chip cohorts suddenly finds itself a net drag on overall S&P 500 performance — which itself surprised investors with a solid 5.5% return.

Nevertheless, generative AI is still hot and slowly moving into real-world applications.

Abby Yoder, US equity strategist at JPMorgan Private Bank, highlighted that healthcare, which is notoriously slow-moving, may be an upcoming candidate for AI-driven innovation.

"Healthcare has underperformed seven of the last eight years," Yoder pointed out in a recent episode of Stocks in Translation, despite the sector being the only one in the S&P 500 to boast positive annual earnings growth over the past 21 years.

But Yoder sees AI as a potential key to unlock a long-awaited shake-up that could bring long-term growth back to the sector.

Healthcare stocks have struggled in recent years, a trend Yoder attributes to legacy constraints of old systems and obstacles that make it difficult for new technologies to take root. The byzantine web of players, rules, regulators, and more has so far prevented significant AI adoption, which has the potential to address inefficiencies in insurance approvals, manual record-keeping, and claims management, all of which drag on productivity.

There are some ripples of change, however. Companies like Google and Microsoft are diving into this space, partnering with hospitals and startups to create AI tools that lighten this burden.

On the diagnostic side, AI is being used to streamline medical imaging, cutting down time for tasks like identifying patterns in medical data, which improves both speed and accuracy in patient care. The goal is not to rid the world of human radiologists and technicians, but empower them with 21st-century tools that lighten their load and accelerate patient diagnoses and recoveries.

AI proponents say it's not just about cutting costs; it’s about revolutionizing patient care. By using vast datasets of clinical information, the promise of AI is to someday help predict patient outcomes more effectively, modeling care before it happens to anticipate complications and select treatments.

The other great hope for medical AI bulls is the immense promise for drug discovery.

According to Morgan Stanley's healthcare forecast, the company's head of US biopharma research Terence Flynn estimates that “[every] 2.5% improvement in preclinical development success rates could lead to an additional 30-plus new drug approvals over 10 years," which would represent around $70 billion.