Artificial Intelligence Responsiveness in Nursing: A Concept Analysis for Advancing Nursing Science.

Authors

Areej Al-Hamad, Yasin M Yasin, Lujain Yasin

Published in

ANS. Advances in nursing science. Sep 01, 2026. Epub Sep 01, 2026.

Abstract

Artificial intelligence (AI) responsiveness in nursing was conceptually analyzed to clarify its defining attributes, antecedents, consequences, and empirical referents. Guided by Walker and Avant's approach, sources on AI literacy, responsiveness, and related nursing concepts were thematically synthesized. Four defining attributes were identified: foundational understanding of AI, critical appraisal of AI outputs, ethical and accountable response, and integration with clinical judgment. Antecedents included exposure to AI-enabled tools, digital and informatics foundations, education and training, and organizational and regulatory support. AI responsiveness supports safer practice, stronger decision-making, ethical care, equity, readiness, and professional nursing accountability.

PMID:
42679093
Bibliographic data and abstract were imported from PubMed on 02 Sep 2026.

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