Nursing outlook · 2026
Evaluating the AI Nurses Network: A cross-sectional survey on the resources and impact of a global network on artificial intelligence in nursing.
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Zhang Mengying, Chong Huimin, O'Connor Siobhan
Аннотация
BACKGROUND: Artificial intelligence (AI) is advancing in healthcare, but nurses' low AI literacy limits its integration into education, research, and clinical practice. The AI Nurses Network was established in 2024 as a global network providing free training, funding, news, and events to support nurses worldwide in developing and applying AI in professional practice.
PURPOSE: To evaluate members' engagement with, and perceptions of, the AI Nurses Network resources, including their use, quality, and impact.
METHODS: A cross-sectional online survey was conducted. Convenience sampling was used, with the survey distributed via the network's communication channels. Data were analyzed using descriptive statistics and subgroup analyses, with qualitative responses summarized to identify key themes.
DISCUSSION: Eighty responses indicated variable engagement across the network's resources. Training quality was rated highly and perceived to improve AI knowledge, awareness, and professional development, although impacts on collaboration, research output, and securing funding were more moderate. Uptake of the funding scheme was low, largely due to lack of awareness and perceived barriers. Communication channels were widely used and positively evaluated for supporting awareness and engagement with AI but had fewer effects on collaboration and research outputs. Interactive events such as hackathons were highly valued for fostering networking and collaboration. Exploratory subgroup analyses found limited evidence of demographic variation (i.e., age, gender, education level) in resource engagement or their perceived impact.
CONCLUSION: This global network supports nurses' engagement with AI by enhancing awareness, knowledge, and professional development, but its impact on collaboration, research outputs, and securing funding is limited due to its early stage of development. This highlights a gap between AI literacy and its practical application in research and evidence-based practice and the need for a more structured and systematic capacity-building pathway for nurses.
PURPOSE: To evaluate members' engagement with, and perceptions of, the AI Nurses Network resources, including their use, quality, and impact.
METHODS: A cross-sectional online survey was conducted. Convenience sampling was used, with the survey distributed via the network's communication channels. Data were analyzed using descriptive statistics and subgroup analyses, with qualitative responses summarized to identify key themes.
DISCUSSION: Eighty responses indicated variable engagement across the network's resources. Training quality was rated highly and perceived to improve AI knowledge, awareness, and professional development, although impacts on collaboration, research output, and securing funding were more moderate. Uptake of the funding scheme was low, largely due to lack of awareness and perceived barriers. Communication channels were widely used and positively evaluated for supporting awareness and engagement with AI but had fewer effects on collaboration and research outputs. Interactive events such as hackathons were highly valued for fostering networking and collaboration. Exploratory subgroup analyses found limited evidence of demographic variation (i.e., age, gender, education level) in resource engagement or their perceived impact.
CONCLUSION: This global network supports nurses' engagement with AI by enhancing awareness, knowledge, and professional development, but its impact on collaboration, research outputs, and securing funding is limited due to its early stage of development. This highlights a gap between AI literacy and its practical application in research and evidence-based practice and the need for a more structured and systematic capacity-building pathway for nurses.