The revenue cycle management (RCM) environment is becoming increasingly complex. Financial pressures mount, regulations change, and new technology arrives at a dizzying pace. How do revenue cycle teams keep up with the change? How do revenue cycle leaders and their teams keep pace?
This was the central conversation at the 2026 AGS Health Revenue Cycle Management Summit, where finance, technology, and HIM leaders discussed how artificial intelligence (AI) is transforming revenue cycle management and what it takes to deliver measurable financial and operational impact.
A Defining Moment for Revenue Cycle Transformation
Patrice Wolfe, CEO of AGS Health, opened the Summit with a perspective that reflects what many are feeling: This is a watershed moment.
She framed it as an inflection point, unlike much of what she has experienced in the industry. Not because the challenges are new—financial pressures, changing reimbursement, and regulatory complexity have always been part of health care. What is new is the pace and scale of AI-driven change layered on top of those persistent challenges.
Adoption is no longer optional. It is critical to sustain revenue cycle performance across the entire lifecycle, from patient access through collections. The question isn’t whether to explore AI solutions, but how to integrate them thoughtfully and pragmatically to improve outcomes and revenue capture through a hybrid intelligence model that combines skilled human expertise with targeted enablement.
Patrice’s framing resonates with anyone whose revenue cycle team is or has ever been overextended.
Why Financial Pressure Is Increasing in Revenue Cycle Management
Consider recent legislation such as the One Big Beautiful Bill Act (OBBBA). In the wake of its passage, hospital revenue could drop by tens of billions nationwide, and net patient revenue for some providers could decline by up to 10%.
Insurance trends are also in flux. Although enrollment in the Federal Marketplace fell by 5% in 2026, these figures don’t accurately reflect actual coverage levels. Individuals have until March 31 to submit their premium payments; those who fail to do so will have their coverage canceled retroactively, which is expected to increase the number of uninsured individuals. The true effect on the overall payer landscape likely won’t be clear until July 2026.
On the payer side, advanced analytics and automation have progressed faster, contributing to higher denial rates. What’s more, many of those denials aren’t appealed because of time and resource constraints. Denial rates are now approaching 20% in many environments, and more than 60% of denials go unappealed, representing a significant, recoverable revenue opportunity. These technologies can help uncover untapped opportunities for revenue recovery if approached strategically.
Applying AI in Revenue Cycle Management
Amrit Saxena, founder and CEO of SaxCap, and Giannis Kremuzas, former Google executive, offered a practical lens on AI adoption. What the hype really means for day-to-day operations is that AI is a tool, not a replacement for skilled staff.
Different technologies serve different purposes:
- Machine learning can predict patterns and uncover risk.
- Deep learning can interpret unstructured clinical notes.
- Generative AI (GenAI) can produce insights that would take humans hours to assemble.
The real challenge and opportunity lie in connecting the right tool to the right workflow. Deploy it without that alignment, and you risk investing heavily without seeing meaningful results.
Where Automation Delivers Value Across the Revenue Cycle
The summit framed AI across the three zones of the revenue cycle: front-end, mid-cycle, and back-end revenue recovery.
Patient Access: The Front Door to Denial Prevention
On the front end, AI-enabled technologies can automate eligibility, registration, and prior authorization, removing repetitive, structured work. These high-volume, structured workflows are delivering immediate operational gains for healthcare organizations. Results reinforce that denial management and prevention start with patient access, with measurable improvements in:
- Turnaround times.
- Patient financial clearance.
- Self-service collections.
In practice, revenue cycle performance is increasingly determined before a claim is ever submitted, making patient access a critical driver of financial outcomes.
HIM and Coding: Augmenting Human Expertise
Mid-cycle processes, such as coding and clinical documentation, are more complex and require careful implementation. Many tasks are unstructured, and technology can facilitate but not fully replace human decision-making in the following areas:
- Accelerate code suggestions and documentation review.
- Improve audit traceability.
- Enable specialty-specific autonomous coding with structured workflows.
This reinforces a familiar reality that technology amplifies efficiency, freeing staff to focus on higher-value work, and success depends on upstream data quality, thoughtful workflows, and operational discipline.
A/R and Denials: Immediate ROI
Back-end processes, including billing, collections, and denials management, offer opportunities for predictive analytics and workflow optimization. Artificial intelligence can:
- Highlight high-risk denials before submission.
- Optimize appeals based on the likelihood of success.
- Recover underpayments through anomaly detection.
Healthcare organizations leveraging technology in these areas have recovered millions while decreasing operational effort. It’s an ideal place to start when first investing in these technologies. Small pilots can create measurable wins and build confidence across your team.
A Pragmatic Approach to Revenue Cycle Automation
One theme echoed throughout the summit is that AI adoption is a marathon, not a sprint. Healthcare organizations must standardize workflows and address process gaps before implementing automation to avoid inefficiencies that scale alongside technology.
The message from panelists was clear:
- Don’t chase each shiny new tool.
- Identify high-volume, high-impact workflows.
- Decide whether to build, buy, or partner.
- Pilot solutions on a manageable scale.
- Measure outcomes.
- Then scale thoughtfully.
For many healthcare organizations, the winning formula is a hybrid approach. Low-risk tasks can be fully automated, medium-risk tasks augmented, and complex tasks remain human-driven. That combination of human expertise and artificial intelligence typically delivers the highest ROI.
If you’ve been cautious, waiting for proof of performance, this advice is reassuring: practical pilots with clear, measurable results can help you move forward without needless risk.
Governance, Security, and Regulatory Uncertainty
A key insight from the Partner Summit is that AI and automation cannot operate in isolation from governance, security, and compliance frameworks. Healthcare organizations must address foundational requirements while navigating regulatory uncertainties that complicate long-term AI planning.
Cybersecurity, regulatory governance, and disciplined execution are non-negotiable. Artificial intelligence must integrate into present workflows, not operate alongside them. Real success comes when technology reduces friction for patients, improves staff efficiency, and delivers measurable financial results.
Key Takeaways for Revenue Cycle Leaders
Innovation for innovation’s sake doesn’t drive outcomes.
The future of revenue cycle transformation lies in the thoughtful, pragmatic application of these technologies, guided by rigorous planning and constant attention to quantifiable outcomes. While there is potential to reduce collection costs by 30% to 60%, that value is realized only when adoption is intentional, disciplined, and aligned to operational priorities.
For healthcare leaders, the summit functioned as both a reality check and a roadmap. AI is no longer theoretical. It’s an operational necessity. Success depends on how effectively organizations align technology with human expertise and embed it into day-to-day workflows.
Key insights from the Summit include:
- Revenue cycle transformation is driven by financial pressure and intelligent automation.
- Denial prevention during patient access can lead to a significant upstream impact.
- Hybrid intelligence of automation with human expertise drives sustainable performance.
- Automation focused on A/R and denials management offers a fast path to ROI.
- Success depends on workflow integration and measurable outcomes tracked through analytics.
Contact us to learn how AGS Health helps healthcare organizations apply AI to improve revenue cycle performance and drive measurable results.
Christina Cussimanio
