When AI Enters the Clinic, Change Isn’t Immediate

AI has expanded beyond just chatbots on your smartphone — it's now widely used in clinics, hospitals and pharmaceutical labs. This growing adoption has introduced new competitors challenging the established companies specializing in health care software and devices.

For example, Anthropic and OpenAI, leading players in the AI world, both launched health care tools earlier this year.¹ These tools aim to assist with patient care, billing and other functions — tasks already managed by many existing software solutions.

Given the complexity of the health care industry, which is heavily regulated to help ensure patient safety, data privacy and other concerns, health care facilities look for trustworthy tools and solutions. This emphasis on trust might benefit established companies. Our team has identified two types of firms that we believe may be well-positioned to succeed in this environment:

1. Companies that integrate AI into their products and services, enhancing their power and value.

2. Companies with deep “competitive moats” — strengths that are hard for new rivals to match.

These firms don’t view AI as an asteroid that could wipe out their industry. They see it as a tool to help boost earnings, support pricing strategies and strengthen customer relationships.

Of course, execution also matters, and these companies could still face tough challenges from AI-centric firms like Anthropic and OpenAI. But we believe it would be premature to write them off.

How Providers Use AI Across Health Care

AI at the Point of Care: Documentation and Imaging

There’s a good chance your doctor used AI during your last visit.

More healthcare providers are adopting ambient clinical documentation. This involves a provider recording audio during a checkup, often using a smartphone or tablet app.

Then an AI tool like Microsoft’s Dragon Medical One transcribes the recording and formats it as a structured report.²

Doctors still need to review the final product for accuracy, but ambient documentation allows them to focus more on patients during visits. They aren’t splitting their attention between asking thoughtful questions and taking notes.

More device makers are also building AI into their scanning and imaging tools.

To date, the Food and Drug Administration (FDA) has authorized more than 1,400 AI-enabled devices for marketing in the U.S.³

About 75% of these devices are used in radiology.⁴ The AI is designed to act as a second set of eyes for radiologists, highlighting abnormalities that humans might miss.

AI technology can also speed up the pace of diagnosis. For example, GE HealthCare reported that its AI-enabled X-ray system shortens the time to identify a collapsed lung by 57%, helping to flag cases for clinician review more quickly.⁵

Why Existing Firms May Have a Head Start in Clinical AI

Software and device companies already integrated into health care workflows may enjoy several advantages when it comes to AI. They understand the intricacies of health care regulations, and in many cases, hospitals and clinics already use their products.

Device makers might have an easier time selling an AI upgrade for their in-use machine than a company that’s new to the field.

We also can’t dismiss the importance of familiarity. Care providers know that software outages and equipment failures can shut down facilities and jeopardize patient care. So, they may prefer to stick with vendors they already know and trust.

AI in the Back Office: Scheduling, Billing and Claims

When you pay your doctor, you’re not just paying for medical care. You’re also paying for the back-office functions that make your appointments and procedures possible.

According to one estimate, administrative costs make up roughly 25% of U.S. health care spending.⁶ McKinsey & Co. believes that using AI tools to streamline billing, scheduling and other tasks could help companies save more than $256 billion annually.⁷

One of the biggest opportunities may lie in revenue cycle management (RCM).

RCM covers the financial aspects of health care – verifying patients' insurance coverage, submitting and processing claims, appealing denials, billing patients and more.

This is a complex process, and many companies believe AI could boost its efficiency. One example is Waystar, a long-standing player in the RCM space.

Why Established RCM Vendors Might Adopt AI More Quickly

More than 1 million health care providers use Waystar’s platform, and the company processes billions in patient payments every year.⁸ As a result, Waystar possesses a formidable amount of data on insurance claims and denials.

Waystar’s AltitudeAI™ analyzes all these past transactions, looking for patterns and learning from them. It can then apply this knowledge to new cases, the company says.

For example, it may facilitate early identification of claims issues, allowing providers to resolve them before submitting them to the insurer.

When claims are denied, AltitudeAI identifies which are most likely to be overturned, so clients can address them first. The tool can also automatically generate appeals to insurers.⁹

With every new transaction, the company says, its AI model gets sharper – an advantage that compounds over time.

“Our data advantage is self-reinforcing,” Waystar CEO Matthew Hawkins said. “Every claim, denial and payment improves our models.”¹⁰

AI in Drug Development: Where Timelines Could Shrink

Pharmaceutical companies spend years developing and testing new drugs before they arrive at your local pharmacy.

Companies are exploring how AI could speed up the timeline. One example is IQVIA, a clinical research organization (CRO) that assists pharma companies in designing and conducting trials for their new treatments.

Launching a trial can take months. CROs must review prior research and write test protocols that will pass regulatory scrutiny. They need to identify and recruit test subjects that meet testing standards.

They must also collect and analyze significant amounts of data from the trial.

Last year, IQVIA and NVIDIA unveiled a suite of AI agents that can independently handle different parts of this process. This could potentially shave weeks off the schedule.¹¹

IQVIA also offers an AI-powered analytics service helping pharma firms analyze trends in prescriptions and drug sales. This information can be critical when a firm is preparing to launch a new drug in the marketplace.

Why Trial Data and Networks Could Create an Advantage

Like Waystar, IQVIA asserts that its data acts as a competitive moat. The company has accumulated this information over many years from pharmacies, health care providers and other partners.

Competitors can’t simply scrape this data off the web, IQVIA CEO Ari Bousbib said. His company has gathered, cleaned and organized the data into a format optimized for algorithmic analysis.

In theory, companies like OpenAI could collect data like this, but not easily.

“We do this at a huge cost and on a massive scale, and we have been doing this for decades,” Bousbib said. “By the way, many have tried to replicate it. No one has duplicated it.”¹²

What Matters Most as Health Care AI Scales Up?

While AI holds significant potential for health care, this trend is still in its early days.

One survey of health care organizations found that many AI projects remain in the ideation and proof-of-concept phases. Only a small number have advanced from pilot projects to full, systemwide implementation.¹³

As AI technology advances, so does the regulatory and legal environment that governs its use in health care. Providers may hesitate to use AI for tasks that directly affect patients’ well-being.

All this means that different companies could experience different outcomes, depending on their niche, execution and competition. Our selective investment strategy analyzes a company’s fundamentals to assess its growth potential.

Health care represents a massive opportunity for AI solutions that can improve care, reduce costs and introduce new treatments. AI firms, startups and others are all fighting for their share of this market.

In our view, many existing firms – those that understand the risks and opportunities of this changing landscape and build sustainable competitive advantages – are likely well-positioned to compete.