Program Description
Artificial intelligence (AI)
has made it possible to automate complex tasks that typically require human
intelligence. AI is already reshaping everyday pharmacy practice by turning
clinical and patient‑generated
data into actionable insights. It can predict which patients are likely to miss
doses, flag high‑risk
drug‑drug interactions, forecast
medication demand to keep shelves stocked, and calculate individualized dose
adjustments, but still requires human oversight. Despite these advances, many
pharmacists and pharmacy technicians are not fully aware of AI concepts in
their clinical training, resulting in gaps in basic AI literacy, limited
ability to critically appraise the validity, reliability, and contextual
appropriateness of AI tools, and confusion around AI solutions. This article
will ensure pharmacists and pharmacy technicians are informed about the
capabilities and limitations of AI in pharmacy while ensuring patient safety,
privacy, and regulatory compliance. A variety of technologies will be discussed
as well as their impact on patient outcomes, pharmacy efficiency, and
feasibility of integration. As medication safety gatekeepers, pharmacists and
pharmacy technicians must be prepared to critically appraise AI technologies to
maintain high ethical and legal standards while remaining in their roles as
coordinators of value‑based,
patient‑centered care in a rapidly evolving,
technology-focused health care landscape.
Target audience: Community and health-system pharmacists,
and pharmacy technicians
Type of activity: Application
Release date: December
1, 2025
Expiration date: December
19, 2026
Learner
level: Intermediate
Time to complete activity: 2.0 hours
Fee: Free
Educational Objectives
At the completion of this activity, participants will be able to:
- Examine core artificial intelligence (AI) and machine learning concepts relevant to pharmacy
- Identify AI-based tools currently validated and used in pharmacy practice
- Explore the role of the pharmacy team in implementing and assessing AI in clinical settings
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