# Integrating Large Language Models Into UAE Community Pharmacies: Pharmacists′ Perspectives on Benefits, Concerns, and Implementation Barriers

## TL;DR

This study examines how UAE community pharmacists view the use of large language models, highlighting concerns and barriers to adoption.

## Contribution

The study provides insights into pharmacists' perspectives on LLMs in UAE pharmacies, identifying key concerns and barriers specific to this context.

## Key findings

- Pharmacists expressed significant concerns about LLMs, including hacking risks and technical failures.
- Higher education levels and future LLM usage intentions were associated with fewer concerns.
- Lack of pharmacy-focused LLM programs and inadequate training were major barriers to adoption.

## Abstract

The UAE′s rapid economic growth and adoption of advanced healthcare technologies necessitate understanding pharmacists′ perspectives on large language models (LLMs) to address implementation challenges and align with the nation′s digital health initiatives.

This study explored UAE pharmacists′ perceived benefits, concerns, and barriers to LLM adoption, as well as factors contributing to heightened concerns in community pharmacies.

A survey‐based cross‐sectional study was conducted among 528 community pharmacists (51.3% female) in the UAE between October and November 2024. Pharmacists completed a validated questionnaire assessing socio‐demographic information, perceived benefits, concerns, and barriers related to LLM use. Binary logistic regression was applied to identify factors associated with concerns about LLMs.

The least‐perceived benefits of LLMs included providing around‐the‐clock support (37.3%), designing personalized care plans (74.4%), and improving patient outcomes (77.0%). Barriers included the need for human supervision (54.7%), insufficient training (32.4%), lack of pharmacy‐focused LLM programs (28.4%), and inadequate resources (28.4%). Key concerns were technical failures or downtime (97.5%), hacking vulnerabilities (97.2%) and limited capacity for empathy, cultural understanding, or ethical considerations in healthcare (95.6%). Increased age was significantly associated with greater concerns (OR = 1.124, p < 0.001). Conversely, pharmacists with master′s or doctoral degrees (OR = 0.483, p = 0.008) and those likely to use LLMs in the future (OR = 0.357, p < 0.001) expressed fewer concerns.

The integration of LLMs into community pharmacy practice faces challenges, including hacking risks, security vulnerabilities, insufficient empathy, and technical failures. Targeted interventions such as enhanced training, robust security measures, and tailored LLM solutions are essential to address these barriers and support safe adoption in pharmacy settings.