By 2030, revenue cycle management will be a digital-first operation, with healthcare provider organizations doubling down on artificial intelligence, automation and analytics to reduce costs and improve billing accuracy.
That's according to the results of a new Everest Group report, supported by Omega Healthcare. The survey is titled, "Realizing the Promise of Tech-Enabled, AI-Driven Revenue Cycle Management: Outsourcing in the New Era." Among its findings:
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85% of senior healthcare executives believe AI will improve efficiencies in RCM operations over the next five years.
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The outsourcing model is shifting from basic revenue management services to AI-powered, outcome-based partnerships.
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The future of RCM will be shaped by generative AI use cases, key barriers to adoption and investment priorities in the coming years.
Anurag Mehta is CEO and cofounder of Omega Healthcare, a tech-enabled services vendor focused on RCM, care coordination and health data curation. The company serves more than 350 healthcare organizations with 35,000 workers in the United States, India, Colombia and the Philippines.
Healthcare IT News sat down with Mehta to dig into the new survey results and discuss the changing RCM landscape at length.
Q. 85% of senior healthcare executives believe AI will improve efficiencies in RCM operations over the next five years. Is this blind optimism or an informed opinion?
A. This level of confidence is informed by direct experience confronting both the challenges and potential of AI in real-world RCM environments. Healthcare providers are navigating a perfect storm of mounting billing complexities, growing patient financial responsibility, staffing shortages and outdated technology systems.
In this context, the promise of AI is not just theoretical – it offers actionable and practical solutions to longstanding inefficiencies across the RCM continuum, from front-end eligibility verification to back-end denial management.
Executives' support for AI is grounded in early results and observable trends. A growing number of providers already are deploying AI-enabled tools like real-time claims tracking, predictive analytics and intelligent automation. These tools have shown improvements in key performance metrics such as reductions in aged accounts receivable, improved charge lag and faster claims resolution.
Furthermore, the survey's respondents weren't tech enthusiasts alone. Rather, they represented a cross-section of C-suite leaders and senior RCM executives who are deeply embedded in operational realities. Their outlook reflects a strategic recognition that AI – particularly generative AI and agentic AI – is rapidly moving from hype to measurable impact.
Q. 51% of healthcare leaders expect an increase in RCM outsourcing budgets by 2030. You suggest linkage between this result and generative AI. Please elaborate.
A. The anticipated increase in RCM outsourcing budgets is closely tied to the integration of generative AI into revenue cycle processes. GenAI's potential is substantial – but it can be complex to implement, requiring advanced data science capabilities, secure infrastructure and regulatory oversight.
As a result, many healthcare organizations prefer to collaborate with third-party vendors that can provide not only the technology but also the operational support and compliance expertise needed to deploy it at scale.
Generative AI is being applied across a wide range of RCM use cases: automated medical coding, clinical documentation improvement via AI scribes, claims analysis to predict denials and more. These capabilities go far beyond traditional rule-based automation, demanding robust platforms and specialist teams.
Strategic outsourcing enables healthcare organizations to fast-track innovation while managing risk. The shift from transactional to strategic partnerships – identified by 71% of survey respondents – confirms organizations no longer are outsourcing just to save costs, but to enable AI-powered transformation.
Q. 51% of providers are actively exploring genAI in RCM. What are they finding? What challenges are emerging, and how can they be overcome?
A. Healthcare providers testing generative AI in RCM are discovering tangible benefits in both operational efficiency and accuracy. Early implementations in areas like eligibility verification, claims analysis and AI-driven chatbots are improving the speed and quality of patient interactions while reducing denials and administrative burden.
For instance, AI-powered documentation tools are streamlining clinical inputs for coding, and genAI is being used to generate insights from unstructured data that previously went untapped.
However, adoption is not without hurdles. The most cited challenge – by about 80% of respondents – is a lack of in-house expertise. Integration with legacy electronic health records systems and concerns over data privacy and regulatory uncertainty also loom large.
To overcome these barriers, many organizations are starting with proof-of-concept projects, implementing rigorous human-in-the-loop validation, and pursuing partnerships to bridge skill gaps. Some are even adopting modular, incremental approaches to EHR integration and leveraging AI as a catalyst for broader information technology modernization.
These steps allow healthcare providers to harness the power of genAI while maintaining control, compliance and alignment with organizational goals.
Q. What else did the survey find that you feel is important to the future of AI in RCM?
A. One of the most compelling findings is the clear roadmap executives are forming around AI as a strategic investment priority. By 2030, AI/machine learning is projected to become the top investment area for RCM leaders, with 66% citing it as a high priority.
This reflects not just enthusiasm but a long-term commitment to AI as a core enabler of financial performance and patient-centric care. The shift signals that AI is no longer an experimental initiative. Instead, it is becoming foundational to how healthcare organizations think about resilience, competitiveness and quality outcomes.
The survey also highlights the rise of agentic AI – an evolution beyond generative AI. These intelligent agents are capable of making decisions, planning tasks and optimizing workflows. Their potential to drive RCM processes, such as prior authorizations or coding from clinical narratives, represents the next frontier in automation.
As regulatory clarity and technology maturity improve, these advanced applications will likely become a central pillar of healthcare financial strategies.
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Email him: bsiwicki@himss.org
Healthcare IT News is a HIMSS Media publication.
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