How AI is solving enterprise revenue cycle complexity

How denial pressure, regulation, payer rules, and AI are reshaping enterprise billing

Revenue cycle management in 2026 looks markedly different than in previous years. The conversation is no longer about incremental efficiency gains or marginal coding improvements. It is increasingly about financial resilience in an environment where denial rates are rising, reimbursement is tightening, and regulatory changes continue to intensify.

For large enterprise billers and health systems, the stakes are higher than ever. Margins are already thin. Payers are changing how they review claims and what they require to approve them. CMS rulemaking cycles are accelerating. And the administrative burden associated with compliance and quality reporting continues to expand.

Revenue cycle management pressure is real, and organizations must do more than incremental improvements in efficiency to thrive.

Denials are becoming more complex and more costly

Industry reporting shows continued growth in clinical validation denials and payer scrutiny around medical necessity documentation, particularly for higher-acuity services and specialty care.¹ Organizations are also facing evolving denial categories tied to documentation precision, prior authorization adherence, and policy interpretation changes.^3,4

Increasing denials are not isolated transaction issues. They are system-wide signals of data quality, documentation consistency, and workflow alignment that must be solved using technology at speed and scale to maintain volume and throughput.

For enterprise organizations that bill for multiple affiliated practices or operate centralized billing functions, even small increases in denial rates can compound quickly. Administrative rework drains staff productivity. Appeals extend days in A/R. Cash forecasting becomes less predictable. The result is operational drag at scale.

Regulatory change is accelerating documentation complexity

The 2026 HCPCS Level II updates and related CMS adjustments underscore the scope of billing, coding, and compliance standards shifts.⁵ New codes, modified definitions, and evolving coverage policies require constant monitoring and system updates.

For enterprise billers, regulatory responsiveness must be embedded into the operational backbone of the revenue cycle – with billing software that can keep up with the changes and update rules, AI logic and automations. 

At the same time, value-based care programs continue to evolve. Participation in quality initiatives requires increasingly granular reporting, accurate risk capture, and coordinated data submission across entities. VBC is fundamentally dependent on clean documentation, timely reconciliation, and coordinated transitions of care. Revenue cycle and clinical documentation are in many ways inseparable in a world of quality programs that bill for and incentivize certain procedures and care adherence. 

In this environment, compliance and performance are intertwined. 

Payers are investing in technology—and raising the bar 

Payers are deploying advanced analytics and automation to identify claim discrepancies and policy misalignment more quickly.⁷ Changes on the payer side – whether private commercial payers or the largest payer in the United States, Medicare and Medicaid – shift the revenue cycle dynamic. The organizations that rely on manual review and reactive workflows are operating at a disadvantage when payers are using automation and algorithms. 

Revenue cycle teams are responding by investing in denial prevention, automation, and predictive analytics.^2,9,10 The shift is toward proactive detection—identifying documentation gaps, coding inconsistencies, or eligibility risks before a claim leaves the system. Our athenaIDX solution has used automation, RPA and AI for years, and continues to build on that industry-leading foundation to operationalize and optimize claims early in the revenue cycle to minimize reactive denial management and rework in complex specialty billing workflows.

Revenue cycle resilience is not about chasing incremental percentage gains. It is about building systems that can adapt, learn, and protect margin as policy, payer behavior, and clinical complexity evolve.

AI is emerging as a structural lever 

Across the industry, automation is increasingly viewed as essential to managing administrative complexity.² But automation alone is insufficient if it is layered on fragmented data. 

The real opportunity lies in AI systems that can read and organize unstructured documentation, reconcile data, surface coding inconsistencies, and prioritize high-risk claims before submission. When AI is embedded early in revenue cycle management, it can reduce manual review time, standardize documentation patterns, and improve claim quality at scale. 

This is particularly relevant for enterprise billing environments, where variation across affiliates and specialties can introduce inconsistency. AI can help standardize interpretation without imposing rigid workflow disruption. 

Importantly, AI is also being deployed to address one of healthcare’s most persistent realities: digital fax volume. Millions of clinical documents continue to move via fax and scanned attachments. AI models capable of labeling, segmenting, structuring, and attaching those documents directly as claim attachments improve data integrity and reduce the downstream administrative burden associated with incomplete documentation.⁶ 

The impact is cumulative: cleaner data in, fewer denials out.

RCM performance is becoming a stabilizer 

As reimbursement pressures persist, RCM performance is no longer viewed purely as an operational function. It is a stabilizing force for organizational strategy. 

Industry trend reports point to growing emphasis on predictive analytics, automation in eligibility and prior authorization, and tighter integration between financial and clinical systems.^2,8 These investments are designed to protect margin and increase resilience in uncertain reimbursement environments. 

Enterprise organizations that can align documentation accuracy, regulatory agility, interoperability, and AI-enabled automation are better positioned to manage volatility. 

Future-proofing the revenue cycle 

The revenue cycle in 2026 is defined by three realities: 

1. Denials are rising in sophistication.
2. Regulatory change is changing past patterns.
3. Data volume is expanding—often without structure.

Revenue cycle resilience is not about chasing incremental percentage gains. It is about building systems that can adapt, learn, and protect margin as policy, payer behavior, and clinical complexity evolve.

For large systems, revenue cycle is a governance function. It aligns documentation, coding, contracting, and collections across hospitals, affiliates, and employed networks to protect margin at scale.

Reach out to our athenaIDX team to learn more about how we can help you handle revenue cycle complexity at scale.