Ethical and Institutional Readiness for Artificial Intelligence in Nursing: An Umbrella Review.

TLDR

The findings show that ethical and institutional issues are closely linked and environments that invested in inclusive leadership, continuous education, and transparent governance demonstrated greater ethical alignment in AI implementation.

Abstract

AIM

This umbrella review aimed to synthesize the ethical and institutional considerations related to the adoption of artificial intelligence (AI) in nursing care.

BACKGROUND

AI is increasingly used in nursing through decision-support systems, predictive tools, and automation. While promising for efficiency and patient outcomes, it also raises concerns about autonomy, privacy, fairness, and accountability. Institutional readiness, including infrastructure, training, and governance, is vital to ensure ethical integration.

METHODS

An umbrella review methodology was used to synthesize findings from systematic, scoping, integrative, and narrative reviews published between 2015 and 2025. Comprehensive searches were carried out in PubMed, CINAHL, Scopus, Embase, and Web of Science. Data were extracted and thematically analyzed to identify recurring ethical challenges and institutional readiness factors.

RESULTS

Thirty-three reviews were synthesized. Key ethical concerns centered on patient autonomy, informed consent, data protection, bias, and unclear clinical accountability. Institutional barriers included limited digital infrastructure, insufficient AI literacy among nurses, and fragmented regulatory oversight. Conversely, environments that invested in inclusive leadership, continuous education, and transparent governance demonstrated greater ethical alignment in AI implementation.

DISCUSSION

The findings show that ethical and institutional issues are closely linked. Environments lacking adequate resources or governance structures tend to amplify ethical risks, while supportive institutions strengthen ethical nursing practice.

CONCLUSION

AI adoption in nursing represents not only a technological innovation but also a fundamental ethical and organizational shift that demands preparedness at both system and practitioner levels.

IMPLICATIONS FOR NURSING PRACTICE AND HEALTH POLICY

Health systems should invest in infrastructure, regulatory clarity, and continuous training. Policymakers should promote equity, transparency, and inclusiveness to ensure that AI enhances patient-centered and ethically grounded nursing care.

TRIAL AND PROTOCOL REGISTRATION

PROSPERO registration number CRD420251060646.