Clinical practices have been integrating AI tools for some time, often through direct vendor relationships. The promise is real: more effective use of physician time, greater operational efficiency, and stronger performance on both the clinical and administrative sides.
A new layer of complexity has emerged as Management Services Organizations (MSOs) begin folding these tools into the service packages they offer to affiliated professional corporations. Determining the fee for AI-enabled services raises a set of regulatory and valuation questions.
Rebecca Simone, a partner in the Nixon Peabody healthcare practice, sat down with two leaders at the center of these questions. Jerry Chang is a managing director and partner at Stout, where he specializes in healthcare valuations for transactions and regulatory compliance, including fair market value advisory related to PC-MSO structures. Michele Masucci is a partner in the healthcare group at Nixon Peabody and, like Rebecca, focuses on healthcare transactions and regulatory compliance with a particular emphasis on digital health, AI, and PC-MSO arrangements.
Together, they walk through the regulatory framework governing these fee arrangements, the valuation challenges that make AI-enabled services unique in the traditional MSO toolkit, and what practices and management companies should be thinking about before they start negotiating.
Key topics covered in their discussion include:
- Fraud and abuse, fee splitting, and corporate practice of medicine: the regulatory frameworks at stake. When an MSO charges a PC for AI-enabled services, Michele explains, these three frameworks don’t operate in isolation. A fee that’s too high can implicate all of them at once.
- How MSO fee levels create legal exposure in PC-MSO structures. The fee can’t just reflect business objectives. If priced too high, it starts to look lik profit sharing, or like the MSO is exerting impermissible control over clinical decision-making.
- Why fair market value of AI-enabled MSO services defies traditional valuation methods. Traditional MSO services are primarily labor and process driven, which are more easily benchmarked against headcount and market compensation data. AI-enabled services introduce intangible assets, including potential intellectual property, into the equation, which don’t fit neatly into traditional frameworks for valuing MSO services.
- FMV factors unique to AI-enabled MSO arrangements, including data value and functional obsolescence. Jerry walks through several factors, starting with what he calls the blurring of traditional boundaries. These factors include the potential of AI-enabled technology interacting with a practice’s clinical functions in ways the corporate practice of medicine doctrine doesn’t permit. He also raises the question of data value, specifically whether a practice that contributes data to the MSO that improves its AI service offering is contributing additional value on top of the negotiated management fee. Additionally, Jerry introduces the concept of “functional obsolescence” and how this could impact the shelf life of an FMV opinion given how fast AI technology is changing.
- Per-click and usage-based MSO fees: billing compliance and claims integrity risks. These structures may seem like a clean way to pass through AI licensing costs, but Michele cautions that when AI-assisted coding leads to higher billing volumes, claims integrity exposure rises. Pairing automation with consistent audits, compliance training, and human oversight mitigates risk. The provider remains responsible, regardless of the tool.
- Unique FMV considerations in AI-enabled MSO arrangements. The necessity of sufficient upfront work to understand how the AI is being utilized in the MSO’s services tops the list. Jerry also flags the risk of MSOs repackaging off-the-shelf tools as proprietary solutions and charging inappropriately. Regarding valuation methods for AI-enabled services, he touches on cost savings approaches, proxy market data, and licensing or subscription structures as emerging alternatives to traditional cost-plus analysis.
- Why legal and valuation teams should engage early in PC-MSO AI structures. Both Michele and Jerry land in the same place: most clients wait too long and don’t fully understand how AI technology interacts with the services being provided by the MSO. Bringing in valuation or legal support after the deal is nearly done risks building a structure that may look good on the surface but may not hold up under regulatory scrutiny or investor diligence.
