Community pharmacists’ acceptance and willingness to adopt artificial intelligence for medication counseling: a cross-sectional study in Jordan

Artificial intelligence is increasingly being incorporated into healthcare delivery. This study aimed to assess pharmacists' perceptions, acceptance, and readiness to adopt Artificial Intelligence (AI) technologies to support medication counseling in community pharmacy practice. A cross-sectional survey was conducted among 300 community pharmacists in Jordan between February and March 2026. Acceptance of AI was assessed using the Technology Acceptance Model (TAM). The survey collected data on perceived usefulness, perceived ease of use, behavioral intention, prior AI experience, perceived benefits, and concerns regarding AI use. Logistic regression analysis was performed to identify factors associated with willingness to adopt AI in medication counseling. This study included a total of 300 community pharmacists. Overall, pharmacists demonstrated positive perceptions of AI technologies. Most participants were familiar with AI tools (n = 283, 94.3%) and reported using them in daily life (n = 222, 74.0%), although most had not received formal AI training (n = 185, 61.7%). More than half were willing to integrate AI into medication counseling (n = 156, 52.0%), while 104 (34.7%) were uncertain and 40 (13.3%) were unwilling. The most commonly perceived benefits were improved patient education (n = 204, 68.0%), drug interaction checking (n = 200, 66.7%), and counseling efficiency (n = 197, 65.7%). Major concerns included inadequate regulation (n = 218, 72.7%), AI accuracy (n = 205, 68.3%), and data privacy (n = 205, 68.3%). Our model demonstrates that behavioral intent is the primary source of willingness to adopt AI (AOR = 1.966, 95% CI: 1.212–3.188; p = 0.006), while younger age was also associated with greater willingness (AOR = 0.947, 95% CI: 0.915–0.980; p = 0.002). Community pharmacists generally viewed AI as a valuable adjunct to medication counseling rather than a replacement for professional judgment. Addressing concerns related to regulation, training, data privacy, and AI reliability will be essential for the successful integration of AI into pharmacy practice.