Ropes & Gray Partner Discusses Agentic AI Healthcare Regulation on AHLA Podcast

Healthcare law partner David Peloquin appeared on the American Health Law Association's Speaking of Health Law podcast to discuss the emerging regulatory landscape surrounding agentic artificial intelligence in healthcare. The episode, titled "Agentic AI in Health Care: Regulatory Uncertainty, Federal Preemption, and Governance Strategies," addresses a critical distinction that legal teams and compliance officers need to understand before deploying AI systems in clinical settings.

The discussion centers on how agentic AI fundamentally differs from earlier AI tools that simply respond to prompts. When most healthcare providers think of AI, they picture systems where a clinician asks a question and receives an answer, then decides what action to take. Agentic AI operates differently—it can take autonomous actions without waiting for human confirmation at each step. This distinction matters legally because liability and regulatory oversight shift dramatically when software begins making independent decisions.

According to the Ropes & Gray announcement, Peloquin covered several key topics during the episode. These included significant use cases currently being observed in healthcare, federal preemption issues related to state AI laws, enforcement risks, and core elements of effective AI governance frameworks. The firm noted that Peloquin recently co-authored an article on this topic in AHLA's Health Law Weekly with healthcare associate Jake Fulton.

The regulatory patchwork emerging across states creates genuine compliance headaches for health systems operating in multiple jurisdictions. Federal preemption questions loom large—whether federal regulations will override state-level AI requirements remains uncertain. This uncertainty forces healthcare organizations to either build governance frameworks that satisfy the strictest state requirements or risk enforcement actions in multiple venues simultaneously. (Nobody wants to explain to a board why they chose the cheaper compliance path.)

From a practical standpoint, the physical reality of implementing these systems involves more than just clicking through vendor contracts. Healthcare organizations need to document decision-making chains, maintain audit trails of autonomous actions, and ensure human oversight mechanisms actually function when systems encounter edge cases. The friction between automated decision-making and regulatory requirements creates tangible workflow challenges that IT teams and legal departments must navigate together.

The AHLA podcast episode was hosted by Andrew Mahler, Vice President of Privacy and Compliance Services at Clearwater, which sponsored the discussion. The episode builds on Peloquin's written work in Health Law Weekly, titled "Paging Dr. Algorithm: Navigating the Regulatory Landscape for Agentic AI in the Healthcare Industry." This multi-format approach—written article plus audio discussion—suggests the topic has gained enough traction to warrant repeated coverage across different media channels.

Enforcement risks represent another critical dimension. State medical boards and other regulatory bodies have begun issuing guidance on AI deployment, though the landscape remains fragmented. Healthcare organizations face the prospect of enforcement actions from multiple regulators with potentially conflicting requirements. The cost of non-compliance extends beyond fines to include reputational damage and potential liability when autonomous systems make errors.

Effective AI governance frameworks need to adapt to this changing environment. Core elements include clear documentation of system capabilities, defined human oversight protocols, and mechanisms for rapid response when systems malfunction or produce unexpected outcomes. The framework must be flexible enough to accommodate regulatory changes without requiring complete overhauls each time a new state passes AI legislation.

Whether healthcare organizations can actually implement these governance frameworks at scale remains an open question. The technology moves faster than regulation, and the legal teams tasked with compliance are often understaffed relative to the complexity of the challenges they face. Building robust governance structures requires investment in both technology and personnel—resources that many healthcare systems are already stretching thin.

The conversation on the podcast reflects a broader industry recognition that agentic AI represents a different regulatory category than traditional clinical decision support tools. This distinction will likely shape how federal and state regulators approach oversight in the coming years. Healthcare organizations that wait for clear regulatory guidance before building governance frameworks may find themselves behind competitors who have already established compliance infrastructure.

For now, the practical reality is that healthcare systems must navigate uncertainty while deploying increasingly autonomous AI systems. The question isn't whether agentic AI will become standard in healthcare—it already is in many settings. The real challenge is building governance frameworks that protect patients, limit liability, and remain functional as regulations evolve. Whether organizations can afford to get this wrong is the question that keeps compliance officers awake at night.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn