Hospital administrative staff show basic-level AI literacy, Turkish study finds

Hospital administrative staff in Türkiye largely understand artificial intelligence at a basic and operational level, according to a qualitative descriptive study published in BMC Health Services Research. Their goal was to examine both the level and the perceptions of AI literacy among a group that has received comparatively little research attention, even as healthcare organizations increasingly integrate AI into everyday operations. When asked what AI literacy meant to them, participants generally described it in terms of basic awareness of AI, simple operational skills, and the ability to use AI applications appropriately.

Rather than framing literacy as a deep technical competency, the administrative staff tended to emphasize familiarity with what AI is and confidence in handling AI-enabled tools correctly. The study also captured how participants perceived AI technologies. Staff mainly viewed AI as a set of tools that enable rapid access to information, support decision-making, provide comprehensive information, broaden perspectives, simplify administrative tasks, and assist with planning.

These perceptions were largely positive, positioning AI as an aid to the information-heavy work of hospital administration. However, positive perceptions did not translate into widespread use. Many participants reported that they did not actively use AI-based applications in their institutions, and the current reported use was largely limited to decision-support systems and the Central Physician Appointment System, known in Türkiye as MHRS, which some participants identified as an AI-supported application.

When the researchers explored the challenges staff faced, they found a notable contrast within the group. Some participants reported experiencing no difficulties with AI, while others acknowledged having limited knowledge and pointed to insufficient institutional guidance. This split highlights an uneven landscape inside a single organization: part of the administrative workforce feels comfortable with the AI tools it encounters, while another part recognizes gaps in its own understanding and lacks structured support from the hospital to close them.

The authors conclude that AI literacy among the hospital administrative staff they studied remains largely at a basic and operational level, with limited integration into strategic decision-making processes. In other words, even where staff appreciate the practical benefits of AI for tasks such as information retrieval and planning, the technology has not become embedded in how the institution makes higher-level administrative decisions. Based on these results, the researchers highlight the need for structured training programs, organizational strategies, and policy frameworks to strengthen AI literacy and support the effective integration of AI into healthcare administration.

Because the study is qualitative, descriptive, and based on 20 participants at a single training and research hospital, its findings describe the experiences and perceptions of this particular group rather than measuring AI literacy levels across the wider healthcare workforce. Even so, the work offers a detailed window into how administrative staff at one Turkish hospital define, value, and currently use AI, and it identifies concrete institutional levers, from training to policy, that could shape how AI literacy develops in hospital administration.

Subject of Research: AI literacy perceptions and use among hospital administrative staff in Türkiye

Article Title: Artificial intelligence literacy among hospital administrative staff: a qualitative descriptive study

Article References: Coşkun, G., & Cankurtaran, Y. (2026). Artificial intelligence literacy among hospital administrative staff: a qualitative descriptive study. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15537-4

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15537-4

Keywords: artificial intelligence, AI literacy, hospital administration, qualitative research, health services, Türkiye, semi-structured interviews, thematic analysis, decision support systems, MHRS, healthcare workforce, training programs