Nurses' Experiences Using AI in Clinical Practice: Systematic Review

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.