AI drug-discovery push in big pharma draws attention as Johnson & Johnson, Merck and Amgen are cited as market beaters

A market roundup published by Yahoo Finance last week urged investors to look beyond Nvidia and instead consider healthcare companies that are applying artificial intelligence to drug discovery. The piece focuses on Johnson & Johnson, Merck and Amgen, describing them as AI-linked biopharma platforms and highlighting what it characterizes as strong stock performance versus the broader market.

The report frames its core comparison around a single, headline number, stating that the selected healthcare stocks are “beating the market by 29 points.” It does not, in the information provided here, clarify the calculation method, the time window, or whether the figure is based on price returns, model ratings, or another specific performance metric.

In addition to performance, the roundup emphasizes shareholder returns. It notes that the companies highlighted pay dividends, positioning cash distributions as an additional element of the investment case alongside their AI initiatives. The report also characterizes their use of AI as aimed at speeding aspects of drug discovery, though it does not provide granular operational details in the material available for this write-up.

The companies named have distinct business profiles within the healthcare sector, but they share the broad theme that AI tools can be used across early-stage research workflows. In general terms, AI in drug discovery is often associated with accelerating parts of target identification, molecule screening, or analysis of biomedical data. Market participants tend to treat these efforts as potentially compounding over time if they reduce the time and cost of moving from hypotheses to candidate compounds.

While the roundup uses Nvidia as a foil, it does not suggest healthcare is displacing semiconductor leadership. Rather, it argues that AI exposure is not limited to data center hardware and instead can show up in biotech and pharma where computational techniques support R&D pipelines. That is an important distinction for investors assessing AI exposure, since the operating drivers and timelines can differ sharply between technology vendors and drug developers.

For sector context, the healthcare market has spent recent years absorbing a mix of AI hype and more traditional biopharma fundamentals, including clinical trial timelines, regulatory review processes, and commercialization trajectories. In that environment, investors often look for a combination of credible technology adoption and financial discipline. The report’s dividend emphasis fits that pattern, even though the dividend details are not specified in the material provided.

What remains unclear from the information available is how the AI initiatives are currently deployed by each company, what near-term milestones are tied to the AI work, and how those initiatives map to revenue or pipeline progress. The roundup also does not spell out what, specifically, moved the “29 points” figure, such as which benchmarks were used or the exact period of outperformance.