Persistent nurse staffing inequities, driven by fluctuating workforce demand, patient acuity, structural bias, and inefficient resource allocation, contribute to burnout, compromised care quality, and inequitable patient outcomes. Advances in artificial intelligence technology offer an opportunity to transform staffing and scheduling decisions by shifting from volume‑based models toward dynamic, equity‑centered workforce optimization. This presentation examines how artificial intelligence‑enabled staffing tools can be responsibly designed, implemented, and governed to promote equitable nurse staffing while safeguarding clinical judgment, workforce trust, and patient safety.