Ask a Revenue Cycle Leader is a new series featuring insights from health system and hospital revenue cycle executives nationwide. Becker’s poses questions on the most pressing issues in healthcare finance — from payer relations and automation to workforce and patient experience. We welcome responses from all revenue cycle, finance and reimbursement leaders.
Question: What does the revenue cycle leader of 2030 need to know that today’s leaders don’t?
Editor’s note: Responses were lightly edited for clarity and length.
Sal Brown. System Vice President of Revenue Cycle at Mount Sinai Health System (New York City): This is one of the most important questions in healthcare today because the RCM leader of 2030 will likely look very different from the revenue cycle leader of 2026. The RCM leader of 2010 was an operator. The RCM leader of 2020 became a technologist. The RCM leader of 2030 will be an orchestrator, managing humans, AI agents, payers and data in a system where the goal is no longer processing transactions, but managing exceptions and maximizing intelligence. By 2030, the best organizations will use revenue cycle as an enterprise intelligence engine. Revenue cycle isn’t back office; it’s one of the most powerful financial levers in healthcare. The next generation of leaders must become data storytellers, not just operational managers; they need to understand APIs as well as AR.
Joel Gentry. Vice President of Revenue Cycle at OU Health (Oklahoma City): Today’s revenue cycle leaders still primarily use AI to support human decision-making. By 2030, that mindset must evolve to recognizing AI as a decision-maker that requires strong governance. Leaders will no longer manage just people and processes — they will oversee intelligent systems that increasingly direct both.
This shift from execution to governance will require a different skill set. Leaders must understand not only what decisions AI produces, but the logic and drivers behind those decisions. As payer and regulatory scrutiny expands beyond human error to include algorithmic behavior, leaders will be expected to explain and defend AI-driven outcomes in detail.
A continuous AI monitoring mindset will be essential. This will not be a static environment; it will require disciplined AI operations, including ongoing model validation, drift detection and audit mechanisms to ensure performance aligns with original intent. Leaders must also proactively identify and mitigate unintended bias to ensure equitable application of AI across the revenue cycle, including payment plans, collections strategies and financial assistance decisions.
By 2030, AI governance will become as critical as compliance itself. The competitive advantage will not come from having the most advanced AI, but from managing it safely, transparently and with discipline at scale.
Desmond Jackson. Vice President of Revenue Cycle at Monument Health (Rapid City, S.D.): The revenue cycle leader of 2030 will need to lead intelligent AI ecosystems rather than simply manage people, processes and technology. Success will depend on understanding AI governance, predictive analytics, automation orchestration and real-time financial decision-making while ensuring regulatory compliance, cybersecurity and ethical use of data.
Next question: What’s one investment in your revenue cycle that paid off faster than you expected? If you are interested in responding, please send responses to Andrew Cass at acass@beckershealthcare.com.
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.
