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The most practical way to think about ChatGPT in pharmacy is draft, verify, sign. The model is good at producing structured, readable text quickly: patient-friendly explanations, counseling points, letters to prescribers, policy and procedure drafts, training quizzes, summaries of long documents you provide, and translations as a starting point for review by a qualified speaker. It saves the most time on writing tasks where the pharmacist already knows the right answer and needs to put it into words. It is least reliable as a source of facts. A widely reported 2023 study from Long Island University, presented at ASHP's Midyear Clinical Meeting, tested the free version of ChatGPT on real drug information questions. Most of its answers were incomplete or inaccurate, and when asked for references it sometimes produced citations that did not exist. General models have a training cutoff, so newer approvals, label changes and shortages may be missing. They also know nothing about your formulary, your patient's kidney function or your state's rules unless you tell them. Verification means checking every clinical statement against authoritative sources. These include the FDA-approved labeling (available through DailyMed), tertiary references such as Lexicomp, Micromedex or Clinical Pharmacology, current clinical guidelines, and primary literature you have actually opened. Any citation the model provides should be treated as unverified until you find the article. Privacy is the other rule. Do not enter protected health information into a consumer chatbot. Some vendors offer enterprise healthcare products under a business associate agreement, but whether a given tool is approved is a question for your organization's compliance team. A common misconception is that removing the name alone de-identifies a case. Dates, rare conditions and locations can still identify a patient.