JMIR Publications

ABSTRACT

Background:

The rapid integration of artificial intelligence (AI) in healthcare is transforming hospital operations and administrative processes. In this context, hospital human resource (HR) managers are increasingly challenged to incorporate AI skills into workforce competencies to support both clinical and administrative functions. However, investigation into HR managers' subjective perspectives remains lacking.

Objective:

To explore hospital HR managers' perspectives on mandating AI skills as essential competencies, with a focus on identifying perceived benefits, challenges, and strategic approaches for effective implementation.

Methods:

A qualitative, phenomenological research design was employed across two tertiary hospitals in Beijing and Sichuan. Purposively sampled HR managers participated in semi-structured telephone interviews, which were audio-recorded, transcribed, and analyzed using Colaizzi's method to extract core themes and subthemes regarding AI competency requirements.

Results:

Fifteen HR managers participated between January 15 and February 9, 2025, including 8 from Beijing and 7 from Sichuan. The participants were aged 34-52 years (mean=42.3). The interviews were 33.9 minutes on average (range: 25-49 minutes). Findings reveal a dual perspective among HR managers: while they recognize the inevitability of AI adoption and its potential to future-proof the workforce and enhance patient care, significant systemic barriers exist. Challenges such as outdated infrastructure and varying levels of workforce readiness were identified. Participants advocated for role-specific, phased training pathways and collaborative approaches to integrating AI skills, rather than enforcing a uniform competency mandate.

Conclusions:

From the perspectives of hospital HR managers, there is a tension between recognizing AI's inevitable role in healthcare's future and acknowledging significant systemic barriers to immediate implementation of universal competency requirements. HR managers advocate for strategic, phased approaches that account for infrastructure limitations, workforce readiness disparities, and the need for role-specific skill development. Successful integration of AI competencies requires balancing technological advancement with organizational readiness, where skill development should evolve alongside infrastructure capabilities.