Most of the conversation about AI in payment integrity is about what the technology can do: driving improved accuracy, efficiency, and scalability. Almost nobody is talking about what happens to the people who were doing that work before the software showed up. When a payer decides to internalize a program, it is not just adopting a tool, it is asking an entire workforce to fundamentally change how it operates, often overnight, and often without a clear model for how that transition should go. This talk argues that the industry has quietly built two separate transformation problems and is only solving one of them. Technology can free auditors and clinicians to do more meaningful, strategic work, but that promise only materializes if organizations treat workforce adaptation as a core design problem rather than an afterthought. Left unaddressed, this becomes a retention and capability crisis: existing staff, many of whom have experienced AI as a threat to their livelihood are asked to acquire new skills with little support, and teams fracture under the strain. Drawing on direct experience helping payers navigate this shift, this session makes the case that the real competitive advantage in payment integrity's AI era will not go to whoever has the best model, but to whoever figures out how to bring their people with them.
In partnership with Machinify
