Healthcare Leaders Optimistic That Automation and AI Will Improve Revenue Integrity

An HFMA survey found that 72 percent of healthcare executives are prioritizing investment in AI and automation for revenue cycle operations, with 46 percent of hospitals already deploying some form of AI in their revenue cycle management. These numbers reflect a clear directional bet from healthcare leadership — and physician practices of all sizes should be paying attention to what it means for the competitive landscape of denial management.

The survey's findings align with a broader reality: revenue cycle management is one of the most data-intensive, repetitive, and pattern-dependent functions in healthcare operations. It is also one of the areas where the gap between well-resourced health systems and smaller physician practices is most consequential.

Where AI Is Being Deployed

The survey identifies several primary areas where healthcare organizations are applying AI to revenue cycle operations:

• Automated coding and charge capture. AI systems that review clinical documentation and suggest appropriate CPT and ICD-10 codes, reducing coding errors that lead to denials.
• Predictive denial prevention. Models that analyze claim characteristics before submission to flag claims at high risk of denial, enabling pre-submission correction.
• Prior authorization automation. Systems that manage the prior authorization workflow, including tracking requirements, submitting requests, and monitoring approvals.
• Appeal generation and management. Tools that draft appeal letters, identify supporting clinical evidence, and track appeal deadlines and outcomes.
• Eligibility verification. Real-time verification of patient coverage and benefits before services are rendered.

The Scale Advantage Problem

The survey results reveal a challenge that physician practices need to confront honestly. Large health systems with dedicated revenue cycle teams and technology budgets can deploy AI tools across millions of claims per year. The 46 percent of hospitals already using AI in RCM are building operational advantages that compound over time — lower denial rates, faster appeals, higher net collection rates.

Physician practices operating with smaller teams and tighter margins face a different calculation. They often lack the claim volume to train custom AI models, the IT infrastructure to integrate sophisticated tools, and the staff bandwidth to manage the implementation. Yet they face the same payers, the same denial patterns, and the same appeal deadlines.

This is the core tension the HFMA survey illuminates: the organizations that most need help managing denials are often the least equipped to deploy the tools that could help.

What 72 Percent Prioritization Actually Means

When nearly three-quarters of healthcare executives say AI is a revenue cycle priority, it signals that the industry is moving past the question of whether AI belongs in revenue cycle management. The question is now how, how fast, and who gets access.

For physician practices, this shift has several practical implications:

First, payers are also investing in AI — but for different purposes. While providers use AI to prevent and appeal denials, payers use AI to identify claims to deny, audit, and recoup. The arms race is real, and practices that do not invest in their denial management capabilities will fall further behind.

Second, the labor market for revenue cycle professionals is increasingly competitive. As health systems deploy AI tools, the role of revenue cycle staff is shifting from data entry and claim scrubbing to exception management and strategic decision-making. Practices that cannot offer competitive technology environments will struggle to attract and retain skilled billing staff.

The Path Forward for Physician Practices

The HFMA survey should not induce paralysis in smaller practices. It should prompt an honest assessment of current denial management capabilities and a clear-eyed evaluation of where technology — whether built in-house, purchased from vendors, or accessed through platforms — can have the greatest impact on revenue recovery.

The practices that will thrive in an AI-augmented revenue cycle environment are those that combine clinical documentation excellence with systematic denial tracking and evidence-based appeal processes. Technology can amplify those capabilities, but it cannot replace the foundational work of documenting care thoroughly, understanding payer requirements, and contesting denials with specificity and rigor.

The 72 percent figure is a signal. The question for every physician practice is whether they are reading it.