Keeping embedded AI accountable as health plans scale

AI is moving deeper into health plan operations, but performance in a controlled test environment doesn't guarantee the same results once that AI is operating at enterprise scale. This shift introduces real operational questions around data security, model drift, and auditability, especially as health plans remain accountable for how AI uses data and how its outputs can be explained and validated.

This video is built for health plan leaders evaluating how to govern AI responsibly as adoption grows. It walks through the core criteria for assessing data traceability and explainability, and outlines how compliance safeguards help plans deploy AI that behaves consistently and can be reviewed with confidence.

See what questions your team should be asking before scaling AI further.