Nurses' Attitudes and Readiness Toward the Integration of Artificial Intelligence in Clinical Practice in Pakistan

Abstract

Artificial Intelligence (AI) is increasingly transforming healthcare delivery, offering opportunities to enhance efficiency, clinical decision-making, and patient safety. However, successful AI implementation in nursing practice depends on nurses' readiness and attitudes toward its integration. Limited data exist on this topic within the Pakistani context. Objective: To assess nurses' attitudes and readiness toward the integration of Artificial Intelligence in clinical practice using the Technology Readiness Index 2.0 (TRI 2.0). Methods: A descriptive cross-sectional study was conducted at a tertiary care hospital in Pakistan from July to December. A total of 90 registered nurses working in inpatient, outpatient, emergency, and critical care units were recruited using non-probability convenience sampling. Data were collected using an adapted version of the TRI 2.0 scale, comprising four dimensions: optimism, innovativeness, discomfort, and insecurity. Each item was rated on a 5-point Likert scale, and composite readiness scores were computed. Reliability was confirmed with Cronbach's alpha (α = 0.88). Statistical analysis was performed using SPSS version 26. Associations between demographic factors and readiness were evaluated using t-tests and a one-way ANOVA, with p < 0.05 as the significance level. Results: Participants had a mean age of 31.6 ± 5.8 years; 81.1% were female, and 70.0% held a Bachelor of Science in Nursing. The overall AI readiness score was high (mean = 3.91 ± 0.54), with optimism (4.12 ± 0.65) and innovativeness (3.96 ± 0.71) showing strong positivity. Moderate discomfort (2.85 ± 0.78) and insecurity (2.72 ± 0.82) indicated manageable apprehension toward AI technologies. Educational qualifications were significantly associated with AI readiness (p < 0.01), whereas gender and experience were not. Conclusion: Nurses in Pakistan demonstrated positive attitudes and high readiness toward AI integration in clinical practice. Educational advancement emerged as a key factor enhancing acceptance and preparedness for AI technologies. Targeted educational interventions and structured training programs are essential to address residual concerns and promote effective, ethical, and confident AI adoption in nursing practice.

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