Managing a “responsibility vacuum” in AI monitoring and governance in healthcare: a qualitative study

Our findings suggest that institutional and cultural forces in healthcare deprioritize the maintenance of AI tools, creating a governance gap that may lead to patient harm and inequitable outcomes. Addressing this responsibility vacuum will require formalized accountability structures, interdisciplinary collaboration, and policy reforms that center long-term safety and equity. Without such changes, AI/ML technologies designed to improve patient health may introduce new forms of harm, ultimately eroding trust in AI and machine learning for healthcare.