Integration of artificial intelligence applications in clinical pharmacy services: A scoping review

Purpose: Artificial intelligence (AI) is increasingly being integrated into healthcare systems, offering new opportunities to enhance the safety, efficiency and effectiveness of clinical pharmacy services. This scoping review aimed to systematically map the current applications of AI in clinical pharmacy practice and to identify the medication-management functions supported by these technologies. Methods: A literature search was conducted following PRISMA-ScR guidelines, covering studies published between 2010 and 2025 in databases such as PubMed, Web of Science and Scopus. Included studies focused on the application of AI in clinical pharmacy services within hospital and community settings. Studies were screened at the title, abstract and full-text levels, followed by data extraction and synthesis. Eligible studies were required to be peer-reviewed, written in English, and to include relevant keywords exploring the intersection of artificial intelligence and pharmacy practice. Results: A total of 36 publications were included in the final assessment and analysis. Most studies focused on AI applications for the detection of drug interactions and adverse drug effects (n = 12, 33.3%), followed by studies for medication errors and potentially inappropriate medications (n = 11, 30.6%). Machine learning techniques, including natural language processing and deep learning, were the most commonly used AI technologies. Conclusions: The development of AI-powered applications and tools for clinical pharmacy services is a promising approach. However, significant efforts, in collaboration with relevant stakeholders, are needed to explore how these AI technologies can add value to clinical pharmacy services in both community and hospital settings.