Integrating Disability‐Informed AI Into Hospital Triage and Clinical Decision‐Making

Artificial intelligence (AI) tools are increasingly used in hospital triage and clinical decision‐making, yet these systems risk perpetuating structural inequities for patients with disabilities if social, institutional, and historical contexts are overlooked. This commentary advances a disability‐informed framework for AI in clinical settings, centering algorithmic justice, epistemic equity, transparency, and inclusive data governance. Authors examine how triage algorithms may misclassify patients with physical, cognitive, sensory, and psychiatric disabilities, explore the implications of technological opacity for clinician and patient authority, and interrogate the assumptions embedded in techno‐optimistic narratives. By discussing participatory data practices and interpretability as ethical imperatives, this work proposes concrete directions for aligning AI with disability justice, making sure that innovation promotes equitable, accountable, and patient‐centered care. Because triage decisions govern access to scarce and time‐sensitive resources, algorithmic misclassification at this stage carries disproportionate consequences for patients with disabilities.