Artificial intelligence (AI) is increasingly being applied to clinical pharmacy tasks that require rapid interpretation of medication, laboratory, genomic, and workflow data, offering the potential for more precise dosing, safer medication use, and more efficient pharmacy operations, although the supporting evidence remains uneven. This scoping review maps the peer-reviewed literature on AI-enabled clinical pharmacy support from 2017 to 2026, with a focus on dosing guidance, medication safety, pharmacogenomic-informed therapy, and workflow automation. Following Arksey and O’Malley’s scoping review framework and the PRISMA extension for Scoping Reviews, searches were conducted in PubMed, Scopus, Web of Science, and IEEE Xplore, and study characteristics were charted for thematic synthesis. The literature shows substantial activity in dosing support and medication safety, particularly in vancomycin precision dosing and adverse drug-event prediction, while pharmacogenomic implementation and workflow automation are smaller but expanding areas; however, most studies remain retrospective, single-site, or developmental. Overall, AI-enabled clinical pharmacy support demonstrates technical sophistication in several domains, yet the field lacks scaled implementation evidence and prospective evaluation of clinical outcomes, highlighting the need for future work emphasizing validation, usability, equity, governance, and integration into pharmacist-led care.