How Will AI Improve on Revenue Cycle Management for Healthcare in 2025?

This year our annual predictions will include some topics that look at how AI could help solve the challenges in our healthcare system. We begin with AI in Revenue Cycle Management. When we look at RCM we can identify these areas; patient check-in, insurance verification and pre-authorization, billing and coding, claims, patient payment and collections, to insurance denials.

We asked our experts what we might see in AI innovations for RCM in 2025. Here is what the experts say. And check out all our prediction posts looking to 2025

Won Andersen, COO, Purchaser Business Group on Health
LinkedIn: Won Andersen

In 2025, we expect to see more market-based reforms in health care price transparency as part of the Consolidated Appropriations Act of 2021. These laws build upon and emphasize the preexisting fiduciary responsibilities employers have, requiring them to seek, understand and use newly disclosed health care pricing and fee information to ultimately lower their health care costs.

Sameer Bhat, Vice President and Co-Founder, eClinicalWorks
LinkedIn: Sameer Bhat

AI solutions are going to take center stage in 2025. 99.9% RCM processes can be fully automated through AI powered agents. We realized that interweaving AI can fundamentally transform revenue cycle management (RCM). For instance, AI-generated eligibility insights curate precise coverage details for specific patient visits and identify potential eligibility issues and deductible information. Furthermore, AI can fully automate the generation of billing coding and manage appeals, saving valuable time and resources. New AI-powered RCM technologies can streamline the end-to-end billing process for healthcare practices of all sizes. These innovations enable independent healthcare practices to manage RCM internally rather than outsourcing, which will help them reduce costs and compete with larger health systems.

Ryan Chapin, Executive Director – Strategic Solutions, AGS Health
LinkedIn: Ryan Chapin

Denials and payer relationships will remain the top challenge for healthcare providers in 2025. Payer requirements will continue growing more complex, leading to an increase in both denial rates and administrative burdens. This, coupled with the ongoing strain due to shortages in the revenue cycle workforce, will lead providers to further integrate AI and predictive analytics into RCM to stay ahead of denial trends by allowing providers to proactively address issues that result in denials and prioritize denials with the highest return on investment.

We’ll also see more payer-facing AI calling technology, with the ability to gather complex information from payer representatives, whether they’re bots or humans. This will streamline tasks within denial management and prior authorization. On the automation front, I expect continued advancement for AI assisting with both clinical and non-clinical appeals, gathering necessary documentation, and drafting appeal letters that humans review before submission.

Michael Combs, President & CEO, CorVel Corporation
LinkedIn: Michael Combs

Earlier this year, the risk management solutions industry’s view on generative AI was skeptical at best. Throughout the year, the skepticism has evolved into optimism, and I expect we will see substantial growth in generative AI offerings in 2025. Optimism around generative AI solutions in risk management will result in significant growth in enterprise solution adoption and implementation.

CJ Cypcar, Vice President, Network Solutions Product Manager, CorVel Corporation
LinkedIn: CJ Cypcar, MBA, CPCU, PMP, CPC

As in all areas, generative AI has the potential to transform bill review in workers’ compensation by streamlining processes and enhancing efficiency. By exploring AI’s capabilities to analyze complex documentation, we aim to empower adjusters to focus more on supporting injured workers and ensuring timely access to care, while also making sure providers are paid promptly and accurately.

Kent Dicks, CEO and Founder, Life365
LinkedIn: Kent Dicks

Consumer-driven care will expand in 2025 as competition increases between traditional healthcare providers and non-traditional entities, such as Amazon and pharmaceutical companies, which are aggressively marketing to consumers to access care on their terms. To remain competitive while still controlling costs, local provider organizations will need to utilize technology and data that ease the burden on clinical staff while still enabling high-quality, prevention-focused care. We expect to see more organizations implementing ‘virtual first’ strategies and utilizing AI and machine learning to identify higher-risk patients, launching proactive clinical interventions before costly emergency department visits or hospitalizations are required.

Rom Eizenberg, CRO, Kontakt.io
LinkedIn: Rom Eizenberg

As the RTLS industry reaches a quarter-century of maturity in healthcare, it will move beyond its traditional focal points of locating assets such as medical equipment and managing staff safety. The last domain, and major growth driver of RTLS in healthcare, will be monitoring and optimizing the patient journey to improve wait times, identify and overcome bottlenecks, and reduce patient stays.

Gary Hamilton, CEO, InteliChart
LinkedIn: Gary Hamilton

In 2025, AI has the potential to transform revenue cycle management by automating insurance verification and eligibility checks, ensuring an accurate view of patient financial responsibilities. As high-deductible plans become more prevalent, practices will rely on AI to streamline pre-visit payment collection and optimize billing workflows, reducing errors and manual intervention. These advancements will not only increase collection rates and financial sustainability for providers but also improve transparency and simplify payment processes. By fostering trust and compliance, AI will enhance the financial experience for patients while supporting operational efficiency for healthcare organizations.

Patty Hayward, General Manager of Healthcare and Life Sciences, Talkdesk
LinkedIn: Patty Hayward

This may be a year of widespread change in healthcare with a new administration and growing adoption of AI solutions, so there will be a lot of pressure on provider and payer organizations to be efficient while continuing to seek opportunities through deployment of new technologies to drive health and operational outcomes. But clinical use cases beyond notetaking are still in need of a wider industry standard for ethics, compliance, and guardrails. So while we likely won’t see widespread use of AI doctors or nurses, payers and providers in 2025 will instead leverage AI to improve operational workflows like patient access, customer service, and claims management at scale to deliver a personalized, frictionless patient/member experience that builds brand loyalty and helps grow revenue.

Bill Kerr, MD, MBA, CEO, Avalon Healthcare Solutions
LinkedIn: Bill Kerr

State legislatures and private health plans will act to dynamite the prior authorization logjam in 2025. This will come through various programs, including requiring electronic PA with decision deadlines, reduced or eliminated PA, “gold card” programs for verified providers and more. Lab Insight solutions will be critical to making informed PA coverage decisions and evaluating provider performance in “gold card programs.

Patrick Murphy, MBA, FHFMA, General Manager, TruBridge
LinkedIn: J. Patrick Murphy, MBA, FHFMA

Healthcare providers face intense pressures from payers and shifting government regulations to meet patient needs and ensure financial stability. RCM must be integrated with the EHR to optimize patient care and support accurate and timely coding, billing, and collections. AI will continue to improve each step for back-office and clinical teams.

In 2025, I anticipate three core areas of focus for AI in RCM:

  • Real-time analytics: Continuously updated information on payer behaviors and nudges to help staff prioritize tasks.
  • Vetted data models: High-quality, unbiased data is critical to building AI systems that reduce administrative complexity instead of adding to it.
  • Third-party validation: Peer-review by industry associations and coalitions must be a top priority. Designations like HFMA peer review is a valuable place to start the search for vetted RCM tools.

2025 brings continued opportunities to fine-tune new technology and go beyond theorizing about AI to practically using these tools and proving success.

Ashish Nagar, CEO, Level AI
LinkedIn: Ashish Nagar

  • Generative AI will revolutionize contact centers by providing agents with real-time, context-aware assistance, leading to 10x improvements in response times and accuracy.
  • AI-powered quality assurance will become the norm, enabling 100% of contact center interactions to be analyzed and scored automatically. Organizations that don’t take this step will be rapidly left behind by their competitors who do.

Stuart Newsome, CPCO, VP of Marketing, Infinx
LinkedIn: Stuart Newsome, CPCO

By 2025, AI in Revenue Cycle Management will become a game-changer, blending tools like cognitive AI, machine learning, and automation to make workflows smoother and more efficient. It’ll help predict and prevent denials by spotting trends in payer history, leading to cleaner claims and faster approvals.

But it’s not just providers leveling up—payers are using their own AI to stay ahead, making it even more crucial for healthcare organizations to adopt these tools.

Success will come down to using AI to boost efficiency and stay compliant while keeping up with ever-evolving payer strategies. The key will be finding the right balance between innovation and regulatory requirements to truly transform healthcare operations.

Nick Patel, M.D., Physician Executive Partner, Pivot Point Consulting
LinkedIn: Nick Patel, M.D.

In 2025, digital transformation in healthcare is set to redefine patient care, making it more predictive, personalized, and efficient. The integration of artificial intelligence and machine learning across healthcare systems allows providers to leverage real-time data analytics for early diagnoses, risk assessment, and treatment optimization. Remote patient monitoring and telehealth have become standard practices, enabling continuous, proactive care that keeps patients out of hospitals and reduces the strain on healthcare facilities. Electronic health records are now interoperable across providers and systems, creating seamless care experiences and reducing redundant tests and procedures. Additionally, advancements in wearable technology and mobile health applications empower patients to take charge of their own health, promoting adherence to treatment plans and lifestyle modifications. The result is a more connected, data-driven healthcare ecosystem focused on value-based care, improved patient outcomes, and a significantly enhanced patient experience.

Nio Queiro, Revenue Cycle Management Advisor, Nextech
LinkedIn: Nio Queiro

With 84% of claim denials deemed avoidable, AI tools are no longer a luxury in revenue cycle management. AI plays an important role in building a stronger financial future, particularly in specialty medicine where payment models are as varied as the procedures themselves. These systems can predict payer behavior, automate appeals, and tackle delays that disrupt cash flow.

Specialty practices, with their unique financial structures, stand to benefit significantly. AI equips providers with tools to offer patients greater transparency and reduce administrative headaches including automated eligibility checks and mobile-friendly payment options. 2025 will bring further opportunities to integrate AI into RCM workflows, especially as back-office teams face new regulations and financial complexities.

Amy Raymond, SVP of Revenue Cycle Operations and Deployments, AKASA
LinkedIn: Amy Raymond

2025 will mark a pivotal year for generative AI (GenAI) in the healthcare revenue cycle. This technology is no longer just a concept discussed at conferences. Innovative healthcare organizations are already implementing it and seeing results.

In 2025, generative AI will continue to redefine how healthcare organizations manage the revenue cycle, shifting from isolated automation efforts to a unified approach powered by clinical intelligence. This technology provides an unprecedented opportunity to address persistent challenges like denials, cost to collect, and coding accuracy. By leveraging generative AI, health systems can unlock the full potential of their clinical data, streamlining workflows and empowering staff with actionable insights. The conversation in 2025 won’t be about whether or not to adopt GenAI — it’s about how to choose the right partner to scale its impact across the organization. The focus will turn to change management, ensuring these investments deliver measurable value. The promise of generative AI isn’t about replacing the workforce; it’s about enabling teams to work smarter. 2025 will be the year we see GenAI technology become integral to the healthcare revenue cycle’s operational and financial success.

Jett Reidy, Chief Product and Technology Officer, EnableComp
LinkedIn: Jett Reidy, MBA

2025 will redefine payer-provider collaboration in specialty claims processing, especially for VA claims. AI-driven platforms will bridge the historical divide between compliance and reimbursement. Through a strong partnership, these intelligent systems complement EHRs to bring alignment across the claims lifecycle while making end-to-end claim transparency the new norm. With faster, more reliable processing, this integration provides veterans with a smoother, more seamless care experience.

Karly Rowe, Senior Vice President of Product Management, Inovalon
LinkedIn: Karly Rowe

In 2025, AI will empower healthcare organizations with the analytics and automation to address the most error-prone areas of the revenue cycle: eligibility, prior authorization, and claims. These areas are currently the most labor-intensive, manual steps in the revenue cycle – and one error can lead to the next, creating further delays in payments or lost collection opportunities due to denials and appeals.

With AI-driven workflows, providers can predict and get ahead of missing, incomplete, or inaccurate eligibility and prior authorization details, and improve claim edits to correct revenue cycle errors in real-time and prevent denied claims. Over the next 12 months, expect to see AI help revenue cycle teams shift from a reactive, manual approach to a proactive, data-driven process that reduces administrative burden, prevents common errors, accelerates access to care, and improves cashflow.

Arnab Sen, Chief Strategy Officer, Omega Healthcare
LinkedIn: Arnab Sen

The next year will bring a fundamental redesign of revenue cycle workflows as AI moves from handling discrete tasks to orchestrating end-to-end processes. Healthcare organizations will increasingly look to partners to help them adopt integrated platforms that combine AI, automation, and human expertise to create more resilient revenue cycles that can adapt to changing payment models and regulatory requirements while improving outcomes.

Lisbeth Votruba, MSN, RN, CAVRN, Chief Clinical Officer, AvaSure
LinkedIn: Lisbeth Votruba, MSN, RN, CAVRN

In 2025, virtual nursing will continue to grow at a cautious pace as hospital leaders recognize that it requires not just investing in new technology, but also organizational alignment, solid change management processes, and buy-in at all levels of the organization. A recent survey found while 74% of hospital leaders believe virtual nursing will be an integral part of patient care, just 10% have standardized virtual care. Hospital and nursing leaders that are taking an intentional, phased approach to virtual care expansion should feel confident that they aren’t alone and there is ample support to help them overcome the challenges that will arise.

Mo Weitnauer, Chief Product Officer, MRO
LinkedIn: Moliehi Weitnauer

In 2025, we will see a greater adoption of many forms of AI to predict, mitigate and prevent denials, particularly those that are driven by clinical mid-rev cycle challenges. This could include solutions such as autonomous coding, AI-enabled CDI, predictive denials and workflow enhancing solutions. Such AI-enabled denial workflow enhancers could include LLM driven appeal letter generators, for example. However, we will continue to see the limitations of AI-only solutions in favor for ‘human-in-the-loop’ solutions. Despite solid advancements in LLMs, there will remain deficiencies in inference and accuracy of AI-only solutions. We will also see that many AI solutions remain focused on narrow slices of the denials issue such as specific outpatient specialties, or types of clinical denial sources such as DRG downgrades. No one solution will be able to rule them all.