Is your AI playing offense or defense?
- Famey Lockwood
- Jun 12
- 3 min read
Published: June 12, 2026
The Healthcare Operating Model for Revenue Cycle Management
is shifting from
recovering revenue to preventing revenue loss
The Healthcare Operating Model for Revenue Cycle Management is changing. Most healthcare organizations are using AI defensively—applying technology after a claim has already been denied.
While these tools have improved denial management and revenue recovery, they are still reacting to a problem that has already occurred.
The next evolution of Revenue Cycle Management is offensive AI: using predictive analytics and intelligent automation before care is delivered to prevent denials from occurring in the first place.
Why Change is Needed:
Prior authorizations:
Initially, health plans had good intentions – prior authorizations (PA) would require health care professionals to obtain advance approval from the health plan before certain prescription medication or medical service could be delivered to the patient. This process would ensure payment to the provider and the patient could receive service without further delay. However, all did not go as planned.
This statement is given by the American Medical Association, “A 2024 American Medical Association survey of 1,000 practicing physicians found that the average practice completes 40 prior authorization requests per physician per week, consuming 13 hours of physician and staff time. Ninety-five percent of those physicians reported that prior authorization delays patient care, and 94% said it contributes to burnout.”
Current Prior Authorization model:
A provider delivers care
The service is coded and claim is submitted
The payer reviews and denies the claim
The provider reacts – rework, appeal, and resubmit
Repeat until one player ends the game
Although providers are using AI in the “rework” phase, and the benefit has been successful, there is a limit to the functionality of the AI model retrospectively. Instead of focusing on revenue recovery “after the fact”, organizations are now starting to shift attention to the start of service by applying AI-driven validation at the point of entry.
Transition to AI Revenue Cycle Model:
Identify authorization requirements before care is delivered
Flag cases requiring prior authorization
Submit documentation to the health plan and obtain approval
Review documentation before claim submission
At this point, a “human” will intervene as necessary and make determinations
AI models can evaluate payer rules, historical denial patterns, authorization requirements, and documentation completeness before a claim is ever submitted.
The value extends beyond reimbursement. Proactive AI can reduce administrative burden, improve cash flow, decrease denial rates, and allow clinical and revenue cycle staff to focus on higher-value activities.
Administrative benefit to predictive AI:
Reduced administrative burden
Improved patient experience
Faster reimbursement
Reduced accounts receivable
Lower denial rates
Less staff burnout
Predictive analytics - at work ... Is your AI playing offense or defense?
Yes, AI is transforming the healthcare environment and the career for the Health Information Professional.
The future of Revenue Cycle Management is not simply faster denial management—it is denial prevention.
Organizations that continue to focus exclusively on post-service recovery are using AI defensively. Organizations that leverage predictive analytics, authorization intelligence, and documentation validation before care is delivered are beginning to use AI offensively.
Human review, governance, and oversight remain essential. As AI becomes more deeply embedded in healthcare operations, the need for information governance, policy development, data quality management, and regulatory oversight will only increase.
Is your AI playing offense or defense? Ultimately, the measure of success is not only fewer denials and improved revenue performance, but also whether providers gain meaningful time back for patient care and whether patients experience fewer delays in receiving medically necessary treatment.
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