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AI's recalibration of the healthcare industry is having an increasingly direct impact on health outcomes, with improvements to the efficacy and efficiency of treatments underpinned by new business models, the emergence of non-traditional actors, and the creation of novel medicines and approaches to expanding healthcare capacity. The resulting shifts in market dynamics will affect issuers' competitive positions and could affect credit quality.

What We're Watching

AI-based technologies' ability to process complex inputs and provide meaningful outputs has already proven its worth across many sectors, spanning real estate to digital publishers and beyond. As adoption accelerates, the healthcare industry stands out as one of the sectors most in need of (and best positioned for) transformation—considering its complexity, the wealth of data it offers, and the significant opportunity for both better health and cost outcomes.

The healthcare sector faces many long-term challenges, including: increasing demand due to growing and aging populations; the unsustainable growth of healthcare costs; increasing physician and nursing shortages; a lack of interconnectivity between patient and medical data; the high medical error rate; health inequalities; the constant need for innovation in pharmaceuticals and medical devices; and the complexity of navigating healthcare systems.

Many of these issues are underpinned by the industry's ongoing reliance on manual processes, which have proven resistant to—but remain ripe for—disruption through automation and innovation. S&P Global Ratings believes generative AI will accelerate the provision of solutions to these challenges. And this view is shared by the industry, as seen in its increasing investment in AI and the widespread application of the technology.

What We Think And Why

We expect AI will disrupt existing healthcare market dynamics by shifting the existing power balance, changing risk-reward calculations for investments and acquisitions, and driving consolidation.

In our view, the first major effects of AI on the healthcare industry will materialize in healthcare services and health insurance. Health insurance is likely to see a reduction in the administrative burden, quicker turnaround on adjudications, and improved healthcare quality. AI promises to benefit healthcare services by creating cost savings and efficiency gains that could significantly augment physicians' capacity, decrease burnout and turnover, improve physician-patient interactions, improve patient satisfaction, and reduce medical errors.

Larger, data-rich healthcare companies will, overall, have an initial advantage in securing these positive outcomes, which could initially widen the competitive gap between companies.

The medical devices, life sciences, and diagnostics subsector could see advances in identifying illnesses, next-generation sequencing, surgery effectiveness, and remote patient monitoring. Meanwhile, pharma and biotech are likely to enjoy enhancements in drug discovery and operating efficiency.

Such technological advancements have already facilitated greater precision in healthcare, with machine learning enabling medical practitioners to leverage data to reveal new treatment approaches and tailor decisions to individual patients.

Those gains also create synergies between biology's wealth of data and AI's input requirements—the combination of which is providing new opportunities for beneficial innovation. At the cutting edge of such outcomes are new capabilities for emerging and innovative research and development.

For example, the application of synthetic biology, known as synbio—a relatively new field of science concerned with reading (sequencing), editing (synthesizing), and writing (printing) DNA to create new entities—is already changing manufacturing, pharmacology, and agriculture. Its influence will continue to spread as genetic innovations and inventions give rise to new applications across renewable energy, healthcare, foods, and crops. Still, such innovation comes with risks, too: AI's ability to automate, accelerate, and scale synbio has the potential to expedite and magnify many of the dangers associated with gene editing.

What Could Change

From a ratings perspective, the medium- and long-term effects of AI on healthcare organizations and, ultimately, credit quality remain uncertain.

In the medium-term, the pace of AI adoption will differ across the healthcare subsectors, including insurers, government payors, service providers, pharmaceutical companies, medical device makers, and life sciences companies. Over the long-term, the acceleration of AI disruption could weaken some companies' competitive positions and lead to downgrades—particularly in the case of companies that fail to implement a cohesive AI strategy and a governance framework that is aligned with their business strategy.

On the biotech front, the combination of AI and scientific developments like synbio are likely to accelerate and deepen the potential for disruption over the next five years or less. AI's implications for the growth of industrial biomanufacturing, support of the circular economy, and expansion of big data in biology will all be key factors to watch.

Writer: Molly Mintz