Artificial Intelligence Technologies in Nursing Clinical Decision‐Making: An Umbrella Review

ABSTRACT

Aim

To describe contemporary peer-reviewed literature on artificial intelligence in nurses' clinical decision-making.

Methods

An umbrella review of literature reviews.

Data Sources

Four major databases were searched for reviews published between 2019 and 2024.

Results

Sixteen literature reviews reported on 965 nursing artificial intelligence primary studies. The studies focused on technology development and emerging performance evaluations, whilst real-world testing or implementation in nursing clinical settings was rare. Rigorous comparative analyses were lacking. While artificial intelligence demonstrates promise in decision-making, challenges such as a lack of controlled studies, algorithmic bias, limited reproducibility and insufficient clinical trials hinder its practical impact. Ethical concerns, transparency and patient data privacy issues pose barriers to AI integration in nursing practice. Ethical and legal guidelines for patient privacy are needed and should be taught along with AI literacy training for nurses.

Conclusions

Artificial intelligence has the potential to enhance clinical nursing decision-making, although evidence is limited by too few examples of nurse participation during development. Underutilisation in administrative nursing functions hinders implementation. Nurses should assume a central role in the design and development of AI applications to ensure that these technologies address the realities of nursing practice. With such improvements, artificial intelligence can transform nursing practice, improve nurses' clinical decision-making and ultimately enhance consumer healthcare outcomes.

Patient or Public Involvement

No Patient or Public Involvement.

Reporting Method

While there is no reporting checklist for umbrella reviews, the PRISMA guide for systematic reviews was followed.