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Accepted for/Published in: JMIR Nursing

Date Submitted: Jan 11, 2026
Date Accepted: May 14, 2026

The final, peer-reviewed published version of this preprint can be found here:

Nurses’ Experiences Using AI in Clinical Practice: Systematic Review

Scott AJ, Zhao Q, Pan JF, Brown BC, Dowding D

Nurses’ Experiences Using AI in Clinical Practice: Systematic Review

JMIR Nursing 2026;9:e91238

DOI: 10.2196/91238

PMID: 42347840

Nurses’ experiences using Artificial Intelligence in clinical practice: A systematic review

  • Ashley JS Scott; 
  • Qimeng Zhao; 
  • Jo-Fan Pan; 
  • Benjamin C Brown; 
  • Dawn Dowding

ABSTRACT

Background:

Artificial intelligence (AI) tools are increasingly used in clinical settings, yet most syntheses focus on nurses’ attitudes or readiness rather than experiences after direct use in practice.

Objective:

To synthesize registered nurses’ experiences of using AI in clinical practice and to identify perceived benefits, barriers, and implementation implications.

Methods:

We conducted a systematic literature review of empirical studies reporting nurses’ experiences of AI use in clinical settings. Searches were performed in CINAHL, Embase, MEDLINE, PsycINFO, and PubMed (last search: September 13, 2023). Two reviewers independently screened titles/abstracts and full texts and appraised included studies using the Mixed Methods Appraisal Tool. We used thematic synthesis with a primarily deductive framework based on Technology Acceptance Model 2 (TAM2), with the addition of facilitating conditions from the Unified Theory of Acceptance and Use of Technology (UTAUT).

Results:

: Twenty studies met inclusion criteria. Perceived usefulness and facilitating conditions were most frequently reported: nurses described AI as supporting decision-making, workflow efficiency, and confidence when implementation included adequate training, interoperability, and technical infrastructure. Ease of use was closely tied to interface design and training. Job relevance and output quality were generally positive when AI aligned with nursing tasks and produced interpretable, reliable outputs. Common barriers included usability issues, limited integration into workflows and electronic systems, privacy and trust concerns, and inconsistent or poorly contextualized outputs. Across studies, nurses often described adoption as conditional on organizational readiness and meaningful involvement of nurses in design and implementation.

Conclusions:

Nurses’ experiences indicate that AI can augment clinical work, but benefits are contingent on workflow alignment, usable interfaces, training, and supportive infrastructure. Implementation strategies should include participatory design with nurses, practical education for safe use, and evaluation in real-world settings to address usability, trust, and governance issues. Clinical Trial: PROSPERO CRD42022308051


 Citation

Please cite as:

Scott AJ, Zhao Q, Pan JF, Brown BC, Dowding D

Nurses’ Experiences Using AI in Clinical Practice: Systematic Review

JMIR Nursing 2026;9:e91238

DOI: 10.2196/91238

PMID: 42347840

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