AI in RCM symposium 2025: Fathom panel recap

At the AI in RCM Symposium in New York (Feb. 27, 2025) – co-hosted by Fathom and Adonis – Andrew Lockhart, CEO of Fathom, Lindsay Mersereau, Associate Partner at McKinsey & Company, and Sameer Sethi, SVP and Chief AI Officer of Hackensack Meridian Health led an executive discussion on AI in revenue cycle management. The conversation covered near-term implications of AI for health systems and a roadmap for reducing administrative burdens and improving care delivery. This recap synthesizes key takeaways and actionable advice from the discussion.

Key takeaways

1. Revenue cycle automation delivers immediate ROI while posing minimal clinical risk, making it a strategic starting point for health systems' AI agendas.
2. Physician satisfaction improves dramatically when ambient documentation pairs with autonomous coding to eliminate administrative burdens.
3. Leading organizations are evolving beyond cost-cutting to leverage AI for competitive advantage in quality, accuracy, and staff development.
4. Organizations that move quickly on AI are seeing real results — early adopters are already capturing market advantages while others remain in planning stages.
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Summary

1. Use cases and trends

Providers face unprecedented operational and financial pressures. Chronic staffing shortages, rising costs and inflation, and increasing quality demands are creating an urgent need for technological solutions across the entire industry. "Things are getting more expensive," noted Sameer. "Sustaining growth, managing margins, and providing the right quality of care can only happen if we bring AI and automation into the mix."

AI transformation requires strategic planning. Before implementing any AI solution, organizations need clarity on their objectives, measures of success, and timelines. Lindsay emphasized the importance of answering questions such as: "What is your roadmap? What are your horizons? What partners do you need?" Without this strategic foundation, providers risk making scattered investments that fail to address core business needs.

Prioritization drives implementation success. Rather than attempting enterprise-wide deployment, leading organizations identify specific processes with the highest potential return from technology. Lindsay advised creating "a list of automation capabilities all the way from RPA to agentic AI" and to "understand what pockets and functions to tackle one by one, like payer escalation, appeal generation, prior authorizations." This targeted approach ensures resources are directed to areas offering the greatest impact.

Revenue cycle is ideal starting point. After evaluating initiatives, many organizations begin with the revenue cycle because of its high transaction volumes and low clinical risk. As Sameer explained, "When we think about AI enablement, we think, 'Will it kill somebody?' In RCM, that's not the case. It's the perfect place to build and experiment."
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2. Clinician experience

Administrative burden contributes significantly to physician burnout. The panel highlighted how administrative demands intrude on physicians' in-office effectiveness and even their personal time. Sameer described his physician family members "writing clinical notes at dinner" with their families, while Andrew emphasized the root cause: "Physicians are being browbeaten about what they should be thinking about at the point of care because of coding and downstream requirements."

End-to-end AI creates a watershed moment for clinicians. When automation handles both documentation capture and coding simultaneously, providers regain significant time and attention. Lindsay advocated for "one record, one touch, one message" to eliminate redundant work, while Sameer described this integration as an inflection point that "allows AI vendors downstream to collaborate [and] takes all that burden out of the healthcare system." This seamless approach creates cumulative benefits that extend throughout care delivery, fundamentally changing the provider experience.
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3. Business cases and outcomes

ROI focus has replaced experimentation. Leaders today demand concrete financial justification before greenlighting projects. Sameer confirmed this shift: "Initially, our approach was about diversification, trying to hit every part of the business. Today, it's about direct ROI. It's very clear to leadership: do not do anything until you see direct ROI."

Substantial cost reduction potential in RCM. Implementing AI in coding and billing processes delivers significant financial benefits through both reduced labor costs and improved accuracy that benefits the top line. Sameer emphasized that "AI needs to be in standard billing. The potential for cost savings around that is 50-70%."

Automation enhances reliability and consistency. AI solutions provide steady performance that maintains quality standards day after day. Sameer observed that technology solutions "don't quit on you, don't have to retrain … and they're getting cheaper."

High performers implement AI for strategic advantage. Organizations that have already optimized their RCM operations view AI not primarily as a cost-cutting measure but as a competitive necessity. Lindsay pointed out that slow adoption of AI will be "more expensive in the long term to play catch up."

Processing speed delivers cascading benefits. AI can handle claims processing at speeds unattainable by manual processes, dramatically shortening revenue cycle times. This acceleration improves cash flow while also allowing staff to address higher-value activities instead of routine processing.
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4. Future outlook

Workforce evolution unlocks higher-value opportunities. While Sameer frankly stated that "the jobs you have today will not exist 5 years from now," the panel emphasized how this represents progress, on balance. AI implementation allows organizations to redirect human talent toward more complex, judgment-intensive tasks. Lindsay noted that providers are "understanding how to embed automation to upskill staff to focus on what's more important, and be more on the offensive, not just focus on blocking and tackling." Tomorrow's RCM professionals will focus on work requiring human judgment, such as exception-handling, strategic analysis, and quality oversight.

AI agents will handle routine orchestration. "All of us will have some kind of AI agent in our pockets," Sameer predicted, describing a future in which administrative friction disappears from healthcare operations. These intelligent assistants will manage tasks such as prior authorizations, appointment scheduling, and more, freeing both staff and patients from bureaucratic burdens.

Early adopter advantages. Forward-thinking organizations are already implementing solutions and capturing competitive advantages, especially in RCM. Lindsay cautioned that providers "will have to work faster at adopting tech" and expressed concern that many "will be in planning mode for too long" while competitors and peers advance.

Problems get solved before they become costly. As AI handles routine processing, Lindsay envisioned a fundamental shift in approach: "swarm the problem as it's happening vs. looking back in retrospect." This move from reactive to proactive problem-solving enables staff to address issues before they impact revenue cycle performance, creating new value that wasn't possible in traditional workflows.

Effective change management requires addressing staff concerns. When implementing AI, leaders should focus on how automation enhances existing roles. The panel suggests asking staff, "What's your favorite part of your job? What would you like to do more of in the day?" to demonstrate how AI can improve their work experience by handling routine tasks.

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