How AI Is Reshaping RCM Economics

By Pankaj Arora, Managing Director, Novistra Capital

The economics of revenue cycle management have changed. Not incrementally, and not only at the margin. The shift is structural, and it is already affecting how operators build RCM businesses, how buyers assess them, and where capital is flowing across the sector.

For decades, the model was straightforward. Large teams of trained delivery staff handled coding, claims, billing, collections, and denial management on behalf of providers. Scale came from headcount. Margin came from delivery efficiency. Growth came from winning contracts and staffing them effectively.

That model is now changing.

AI is beginning to reconfigure the underlying economics of RCM delivery. The operational shift is increasingly visible at the workflow level. Eligibility, prior authorization, coding validation, denials, AR follow-up, and underpayment recovery are moving from fragmented human handoffs toward more continuous, system-led execution. As these workflows become less dependent on manual throughput, the economic model begins to change.

The break in unit economics

This is not simply an efficiency story. AI-enabled and agentic RCM platforms are not just doing the same work with modest productivity gains. In many cases, they are operating with a meaningfully different cost structure.

In our conversations with operators and private equity sponsors active in the space, one theme comes up consistently: AI-led platforms are running with materially fewer full-time employees relative to the volume of work processed. Tasks that once required large teams can increasingly be handled through automated workflows, with human specialists focused on exceptions, appeals, complex payer interactions, and judgment-heavy decisions. That changes the model.

Traditional RCM outsourcers have historically operated within a relatively predictable EBITDA margin band, shaped by the labor intensity of delivery. AI-enabled operators are beginning to outperform that range. In some cases, their margin profile is beginning to show more scalable, platform-like characteristics than traditional labor-led services models.

Revenue per employee shows the same pattern. The advantage is not necessarily pricing. It is throughput. These businesses are processing more work per person, with a larger share of routine activity handled by automation rather than manual effort.

A valuation bifurcation, not just a premium

That distinction now matters in valuation.

What we are seeing is not simply a market willingness to pay a technology premium for otherwise similar businesses. It is a growing separation between two different types of RCM asset.

On one side are operators using AI to improve a fundamentally labor-based delivery model. On the other are businesses whose delivery architecture is increasingly built around automation, with human teams supervising workflows and handling exceptions. Buyers are not valuing those businesses the same way.

The most useful lens is not services versus software in absolute terms. It is whether the business still scales primarily through labor, or whether it is beginning to scale through technology.

That distinction is becoming more visible in process. Sponsors that once led diligence around retention, backlog, and staffing efficiency are now asking a different set of questions. 

• How much of the workflow is automated? 
• Where does human intervention still sit? 
• How do margins change as more revenue is migrated onto the platform? 
• What does the operating model look like at scale?

Increasingly, buyers are looking for evidence of automation maturity at the workflow level. 

• Which parts of the revenue cycle are already in production versus still in pilot? 
• Where are agents executing end-to-end rather than merely supporting human teams? 
• How are exception handling, compliance oversight, payer-rule updates, and human review governed? 
• And critically, are improvements visible in operating metrics such as clean claim rates, denial rates, AR days, and coding quality?

The underwriting has shifted because the economics have shifted.

What buyers are now underwriting

For the most active buyers, margin expansion is no longer being underwritten mainly through headcount leverage or procurement synergies. Increasingly, it is being underwritten through automation maturity.

The traditional roll-up thesis in RCM still exists: acquire fragmented operators, consolidate delivery, and improve margins over time. But for the strongest platforms, the more compelling thesis now looks different. Acquire a business with credible automation capability, add revenue and customer relationships through M&A, and migrate that volume onto a more scalable delivery infrastructure.

That is a more powerful form of operating leverage than labor-led consolidation alone.

Alongside automation, buyers are also placing greater weight on defensibility. Proprietary data, workflow intelligence, and payer-specific learning loops are becoming more important. So is the quality of the human-machine model itself – not just how much is automated, but where automation is applied well and where specialist judgment still matters. Both will become more important valuation questions over time.

What this means for deal structure

This shift has practical implications for transactions.

Businesses that can demonstrate strong automation depth, high revenue per employee, and credible margin expansion are increasingly able to position themselves against a different set of comparables. The conversation begins to move beyond traditional BPO valuation frameworks and closer to AI-enabled services or platform-led healthcare workflow businesses.

For more traditional operators, the question is different. Buyers want to understand whether the business can be migrated onto a more automated model, how long that will take, and what investment is required. In those cases, the automation roadmap is not a side issue. It is central to the deal thesis.

For sponsors building RCM platforms through acquisition, this creates a clear playbook. The platform investment establishes the technology and delivery architecture. Add-on acquisitions bring in customers, contracts, and specialist capabilities. The value creation comes from migration: moving acquired revenue from labor-led economics to platform-led economics over the hold period.

What comes next

The RCM market is entering a period of reallocation. Capital is increasingly flowing toward operators that have already built, or are credibly building, AI-enabled and automation-led delivery models. Businesses with strong customer relationships but limited automation capability remain important, but they are more likely to be viewed as acquisition targets than as premium standalone platforms.

The underlying unit economics of AI-led RCM are beginning to diverge from the traditional model. Buyers can see the divergence, investors are underwriting to it, and M&A activity is beginning to reflect it.

This dynamic is not isolated to healthcare. Across BPO and tech-enabled services more broadly, a similar reallocation is underway – driven by AI-enabled execution, domain specialization, delivery resilience, and cross-border scale. We recently explored those forces in detail in The Five Forces Shaping the New BPO.

For a workflow-level view of how Agentic AI is being deployed across the revenue cycle, read Novistra Capital’s companion sector brief, Agentic AI in RCM: From Automation to Execution. In the next article in this series, we turn to the demand side: why more of the revenue cycle is moving toward outsourced specialists, and what that means for the future size and shape of the market.

Pankaj Arora is a Managing Director at Novistra Capital, focused on healthcare services, BPO, and tech-enabled services M&A advisory. He is based in Bangalore, India.