Artificial Intelligence (AI) in the Nursing Profession in Germany

Nursing professionals are critical to healthcare system functioning but face demanding working conditions characterized by high physical and emotional strain, severe staff shortages, and elevated rates of sickness absence. Artificial intelligence (AI) is increasingly discussed as a transformative technology that could provide support and relief in healthcare professions as in other areas. However, empirical evidence on its actual adoption and impact on working conditions on nursing professionals remains limited.

To address this topic, we draw on data from the 2024 German survey on digitalization and change in employment (DiWaBe 2.0) including approximately 9800 respondents, with a nursing subsample of 165 respondents. Analyses included descriptive comparisons between nursing professionals and other professions, as well as regression models examining relationships between AI use and work characteristics, such as work intensity, decision latitude and social support, within the nursing subsample, controlling for demographic factors.

Nursing professionals reported substantially lower AI adoption compared to other professions. When nurses did use AI, applications focused primarily on text processing and diagnostic functions, though usage intensity remained notably lower across all categories. Most AI tools used by nurses were employee-initiated rather than organizationally implemented. Nurses also reported lower perceived benefits from AI. Regression analyses showed positive associations between AI use and both decision latitude facets, which remained significant even after controlling for demographic variables. However, these associations became non-significant when accounting for organizational clustering, suggesting that workplace-level factors may drive the observed relationships more than individual AI use. No associations were found between AI use and work intensity or workplace social support.

This study provides empirical evidence on AI adoption across diverse nursing contexts and use cases, moving beyond isolated implementation studies. The findings hint towards a gap between AI's theoretical potential and its current impact on nursing work quality as well as the importance of technology implementation that incorporates human-centred design principles that preserve professional autonomy and decision-making authority.