AI in healthcare finance is no longer theoretical—it’s operational. And increasingly, it’s measurable.

Waystar (Nasdaq: WAY) has been named an Inc. Best in Business honoree in the Best AI Implementation category, recognition that underscores the growing traction of its AI-powered revenue cycle platform, AltitudeAI™.

The award from Inc. highlights execution—not experimentation. And in healthcare payments, execution is everything.

$15.5 Billion in Denials Prevented

According to Waystar, since launching AltitudeAI, its clients have:

• Prevented $15.5 billion in claim denials

• Achieved 95% time savings in denial prevention workflows

• Increased denial overturn rates by double digits

For revenue cycle management (RCM) leaders, those numbers aren’t abstract. Claim denials are one of the most persistent financial drains in healthcare. They slow cash flow, increase administrative overhead, and frustrate patients who get caught in billing confusion.

The ability to prevent denials—not just respond to them—signals a shift from reactive RCM to predictive automation.

CEO Matt Hawkins framed the recognition as validation of client outcomes rather than product ambition, pointing to the company’s longer-term goal: building what it calls the industry’s first autonomous revenue cycle.

That’s a bold claim in a sector crowded with AI-enhanced RCM platforms from both incumbents and well-funded startups. But Waystar’s differentiator, it argues, lies in where its AI operates.

AI Embedded in the Flow of Dollars

Unlike bolt-on analytics tools, Waystar positions its AI within what it describes as a mission-critical system of record—embedded directly in claims, denials, and payment workflows.

In practice, this means AI agents don’t just surface insights; they act. They identify potential denial risks before submission, recommend corrective actions, and help close the loop on payment.

The system is powered by a proprietary data asset that unifies financial, clinical, and administrative intelligence at scale. Each claim, denial, and payment feeds the models, creating what the company describes as a self-reinforcing learning loop.

That data density may be its competitive moat. In healthcare AI, access to real-world transaction volume often determines whether models generalize effectively—or stall in pilot mode.

Scaling for Large Health Systems

One customer example cited is Advocate Health, a large nonprofit health system operating across the Midwest and Southeast. The organization uses Waystar’s platform to streamline administrative workflows while scaling operations.

As health systems consolidate and expand, administrative complexity grows alongside patient volume. Automation isn’t a luxury—it’s infrastructure.

For large providers, denial prevention at scale can mean tens or hundreds of millions in preserved revenue annually. It also directly impacts patient experience, reducing surprise bills and prolonged payment disputes.

AI in RCM: From Buzzword to Baseline

The recognition comes amid an acceleration of AI adoption across healthcare finance. Revenue cycle teams are increasingly turning to machine learning for coding accuracy, eligibility verification, prior authorization automation, and denial management.

But the market is separating into two camps:

1. Tools that assist staff with incremental productivity gains

2. Platforms that redesign workflows around AI agents and automation

Waystar is clearly positioning itself in the second category.

The broader implication for the healthcare payments ecosystem is significant. If autonomous RCM becomes viable, it could compress administrative costs, improve provider margins, and ease financial friction for patients.

However, as with any AI-driven healthcare system, long-term differentiation will depend on data integrity, regulatory compliance, and measurable ROI—not just automation claims.

Recognition with Real Stakes

Inc.’s Best in Business Awards focus on demonstrable business impact, with submissions reviewed by its editorial team. For Waystar, the distinction reinforces its positioning as a category leader in AI-driven healthcare payments.

More importantly, it signals that AI in revenue cycle management is entering a results-driven phase.

The industry conversation is moving past whether AI can help. The question now is how autonomously it can operate—and how reliably it can protect billions in provider revenue.

If Waystar’s reported numbers hold, autonomous revenue cycle management may not be far off.

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