Hospital Human Resource Managers' Perspectives on Organizational Readiness for Generative AI Skills: Qualitative Descriptive Study.

Background: Generative AI (GenAI) is increasingly entering health care through documentation support, communication tools, educational content generation, and other knowledge-intensive functions. However, organizational adoption remains uneven, and concerns related to privacy, security, output reliability, governance, workflow fit, and infrastructure continue to limit broader implementation. Although the literature increasingly discusses the skills health care workers may need in the GenAI era, less is known about how hospital managers view the organizational readiness required before such skills can be expected across the workforce. Hospital human resource (HR) managers are especially important in this regard because they are involved in training, competency development, workforce planning, and organizational change. Objective: This study aimed to explore how hospital HR managers perceived the relevance of GenAI-related skills, the organizational barriers to broader implementation, and the forms of preparation they considered realistic in the current stage of adoption. Methods: We conducted a descriptive qualitative study in 2 tertiary hospitals in China-1 in Beijing and 1 in Sichuan Province. Purposive sampling was used to recruit HR managers involved in staffing, training, competency development, or workforce planning. Semistructured telephone interviews were conducted between January 15 and February 9, 2025. Interviews were audio-recorded, transcribed verbatim, and analyzed using inductive thematic analysis. The researchers familiarized themselves with the transcripts, generated initial codes, grouped related codes into categories, and developed themes through iterative comparison, team discussion, and refinement. Rigor was supported through reflexive memoing, audit trail documentation, team debriefing, and participant validation. Results: Fifteen HR managers participated. Participants did not describe mature or formalized GenAI competency systems within their institutions. Instead, they described an early-stage organizational environment characterized by strategic recognition of GenAI, informal and uneven experimentation, uncertain governance, and substantial variation in readiness across roles and settings. Three themes were identified: (1) GenAI was viewed as increasingly inevitable and relevant to hospital work, but not yet as a stable universal competency requirement; (2) organizational unreadiness, including infrastructure limitations, lack of approved systems, unclear policy boundaries, and workforce heterogeneity, constrained any move toward universal mandates; and (3) participants preferred phased, role-specific preparation over immediate compulsory standards. They emphasized that readiness depended on secure access, governance, workflow alignment, and differentiated training pathways rather than broad top-down requirements. Conclusions: Hospital HR managers perceive GenAI as increasingly important but not yet governable through universal competency expectations. Their accounts suggest that hospitals are not simply deciding whether to adopt GenAI, but are negotiating when, for whom, and under what safeguards GenAI-related skills become legitimate workforce expectations. Readiness-based, phased, and role-specific approaches may therefore be more appropriate than premature competency mandates in the early stages of hospital GenAI implementation.