By 2030, revenue cycle management will be digital-first operation, with healthcare provider organizations doubling artificial intelligence, automation and analytics to reduce costs and improving billing accuracy.
This is according to the results of the new Everest Group report supported by Omega Healthcare. The survey titled “Technologically-Responsive, AI-Driven Revenue Cycle Management: Realizing the promise of a new era of outsourcing.” In its findings:
85% of senior medical executives believe that AI will improve the efficiency of their RCM operations over the next five years.
The outsourcing model has moved from a basic revenue management service to an AI-powered outcome-based partnership.
The future of RCM will be shaped over the next few years by generation AI use cases, key barriers to adoption, and investment priorities.
Anurag Mehta is CEO and co-founder of Omega Healthcare, a technology-enabled service vendor focused on RCM, care coordination and health data curation. The company serves more than 350 healthcare institutions with 35,000 workers in the US, India, Colombia and the Philippines.
Healthcare IT News We sat down with Mehta to dig into new findings and discussed at length the changing RCM landscape.
Q. 85% of senior medical executives believe that AI will improve the efficiency of their RCM operations over the next five years. Is this blind optimism or an informed opinion?
A. This level of confidence is informed by the first-hand experience of facing both the challenges and possibilities of AI in a real RCM environment. Healthcare providers are navigating the complexity of claims, increasing patient financial responsibility, understaffing and a complete storm of outdated technical systems.
In this context, AI promises are not theoretical and provide a practical and practical solution to the long-standing inefficiency of the entire RCM continuum, from front-end eligibility verification to back-end rejection management.
Executive support for AI is based on early results and observable trends. More and more providers are already deploying AI-enabled tools such as real-time claim tracking, predictive analytics and intelligent automation. These tools show key performance metric improvements, including reduced accounts receivable, improved charging delays, and faster bill resolution.
Furthermore, technology enthusiasts were not the only respondents to the survey. Rather, they represented a cross-section of C-Suite leaders and senior RCM executives, deeply embedded in operational realities. Their outlook reflects the strategic perception that AI (particularly generative and agent AI) is rapidly moving from hype to measurable impacts.
Q. 51% of healthcare leaders expect an increase in RCM outsourcing budgets by 2030. We propose a link between this result and the generated AI. Please explain in detail.
A. The expected increase in RCM outsourcing budgets is closely linked to the integration of generated AI into the revenue cycle process. The possibilities for Genai are pretty big, but they are complex to implement, requiring sophisticated data science capabilities, secure infrastructure and regulatory oversight.
As a result, many healthcare organizations prefer to work with third-party vendors who can provide not only technology but also the operational support and compliance expertise needed to deploy it at scale.
Generated AI has been applied across a variety of RCM use cases, including automated medical coding, improved clinical documentation via AI Scribes, and analysis to predict rejection. These capabilities go far beyond traditional rule-based automation, requiring a robust platform and a specialized team.
Strategic outsourcing allows healthcare organizations to quickly track innovation while managing risks. The transition from transactions to strategic partnerships identified by 71% of survey respondents ensures that the organization is not outsourced just to save costs, but enables AI-powered transformation.
Q. 51% of providers are actively investigating RCM's Genai. What are they finding? What challenges are emerging and how can you overcome them?
A. Healthcare providers testing generated AI with RCM are discovering tangible benefits in both operational efficiency and accuracy. Early implementation in areas such as eligibility verification, claims analysis, and AI-driven chatbots reduces rejection and administrative burdens while improving the speed and quality of patient interactions.
For example, AI-powered document tools streamline clinical input for coding, and Genai is used to generate insights from previously unexplored unstructured data.
However, recruitment is not without hurdles. The most cited challenge by approximately 80% of respondents is a lack of internal expertise. Concerns about integration with Legacy Electronic Health Records Systems and data privacy and regulatory uncertainty are also looming.
To overcome these barriers, many organizations are pursuing partnerships that start with proof of concept projects, implement strict human loop verification and bridge skills gaps. Some employ a modular, progressive approach to EHR integration, and use AI as a catalyst for the modernization of a wider range of information technology.
These procedures allow healthcare providers to leverage the power of Genai while maintaining control, compliance and integrity with organizational goals.
Q. What other research suggested was important for the future of RCM AI?
A. One of the most compelling findings is the formation of clear roadmap executives that are formed around AI as a strategic investment priority. By 2030, AI/machine learning is projected to be the largest investment area for RCM leaders, with 66% citing it as a high priority.
This reflects not only enthusiasm, but also its long-term commitment to AI as a co-ay neebler in financial performance and patient-centered care. The shift indicates that AI is no longer an experimental initiative. Instead, it forms the basis for how healthcare organizations think about resilience, competitiveness and quality outcomes.
The study also highlights the rise in agent AI (evolution beyond the generation AI). These intelligent agents can make decisions, plan tasks, and optimize workflows. The possibility of driving the RCM process, such as advance approval or coding from clinical stories, represents the next frontier of automation.
As regulatory clarity and technology maturity improve, these advanced applications can become central pillars of healthcare financial strategies.
LinkedIn: Follow Bill Siwicki's Bill hit report
Please email him: bsiwicki@himss.org
Healthcare IT News is a publication of HIMSS Media.
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