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Nurses' Experiences Using Ai In Clinical Practice: Systematic Review.

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Nurses' Experiences Using Ai In Clinical Practice: Systematic Review.

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Nurses' Experiences Using AI in Clinical Practice: Systematic Review.

Ashley J S Scott^1,2, Qimeng Zhao¹, Jo-Fan Pan¹

¹Division of Nursing, Midwifery and Social Work, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester, England, M13 9PT, United Kingdom, +44 161 306 9966.

|June 25, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

Registered nurses find artificial intelligence (AI) helpful when it supports decision-making and workflow, provided there is adequate training and system integration. Successful AI adoption hinges on usability, organizational readiness, and nurse involvement in design.

Keywords:

PRISMA artificial intelligence clinical practice decision support systems implementation nursing systematic review technology acceptance model user experience

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Area of Science:

Nursing Informatics
Clinical AI Implementation
Human-Computer Interaction

Background:

Limited research synthesizes registered nurses' direct experiences with artificial intelligence (AI) in clinical practice.
Existing studies often focus on attitudes or readiness rather than post-implementation use.

Purpose of the Study:

To systematically review and synthesize registered nurses' experiences using AI in clinical settings.
To identify perceived benefits, barriers, and implications for AI implementation in nursing.

Main Methods:

Systematic literature review of empirical studies on nurses' AI use in clinical settings.
Searches across major databases (CINAHL, Embase, MEDLINE, PsycINFO, PubMed).
Thematic synthesis using the Technology Acceptance Model 2 and unified theory of acceptance and use of technology.

Main Results:

Perceived usefulness and facilitating conditions (training, interoperability, infrastructure) were key benefits.
Barriers included usability issues, poor integration, privacy concerns, and unreliable outputs.
Nurse adoption was conditional on organizational readiness and involvement in AI design.

Conclusions:

AI can augment clinical work, but benefits depend on workflow alignment, usability, training, and infrastructure.
Involving nurses in AI co-design and refinement is crucial for positive experiences.
Facilitating conditions like training and organizational readiness are primary determinants of AI acceptance.