Pharmacy education faces more challenges because healthcare systems are more complex, medication management is harder, and patient care expectations are rising. Traditional training is important but often can’t keep up with these changes in a cheap and easy way. CAIAs can help by offering interactive and personalized learning that students can use anytime and anywhere.
A recent review looked at 961 studies from 2020 to 2025 about CAIAs in pharmacy education. Only six studies fit the requirements to evaluate CAIAs in this area, showing that this research is quite new. Five of these studies came from English-speaking countries, mostly from the United States. This shows interest in using conversational AI in pharmacy training is starting to grow in the U.S.
The types of CAIA uses found in these studies focused on three main areas:
These areas are important parts of pharmacy education to improve healthcare results and readiness.
The studies showed several features that many CAIAs share for pharmacy education:
These features are meant to make training more flexible, interesting, and effective.
To understand and improve CAIAs, researchers made an evaluation method based on the WHO’s digital health framework. This method groups important development and assessment parts into clear categories.
This approach helps to compare different CAIA programs and guide improvements.
The six reviewed studies were done at different stages of CAIA development in pharmacy education:
The results showed that few people have used these AI systems yet because the technology is still new for pharmacy education. But some positive signs appeared, like learners feeling more confident, better communication skills, and improved knowledge.
These results suggest that CAIAs could make pharmacy education better if more research and development happen.
There are a few reasons why CAIAs are not widely used yet:
Solving these problems is key to using conversational AI in healthcare education more fully.
Artificial intelligence is also used in healthcare outside of education. It can automate many tasks to make work faster and reduce paperwork. AI tools handle scheduling, patient communication, insurance claims, and medical papers.
In pharmacy practice and education, AI automation helps by:
Some companies, like Simbo AI, offer AI phone automation that answers calls and sorts them out. This frees staff to do more clinical and training work. When paired with CAIA training, these AI tools provide a complete way to manage pharmacy work and education.
Health practice administrators and IT managers in the U.S. can use AI tools like these to make work smoother and better support pharmacy education.
Pharmacy education in the United States must match health system goals to improve patient care with skilled workers. Using conversational AI agents offers a way to meet these goals by:
Pharmacy owners and healthcare managers in the U.S. can think about adding these tools to ongoing professional development. This can help meet patient needs, deal with staff shortages, and follow education rules.
Even though few use CAIAs now, the technology fits in with ongoing digital changes in healthcare education and work. Future studies should look at adding group learning, tracking interactions better, and linking CAIAs with electronic health records for more personalized training.
Testing the WHO framework in different pharmacy settings will also give more proof for wider use. Medical leaders and IT managers should watch these changes carefully since they can change training and operation in pharmacies.
Conversational AI agents can help pharmacy students gain confidence, knowledge, and communication skills. Using the WHO digital health framework to develop CAIAs gives a clear and effective way to measure results. When combined with AI tools like Simbo AI’s phone automation, these technologies can improve pharmacy work and education in the U.S.
Medical practice managers, owners, and IT staff can use these tools to cut costs, improve training, and support ongoing learning. Together, these approaches help meet increasing demands on pharmacy professionals and improve the health system overall.
By understanding and using conversational AI in pharmacy education and workflow tools, healthcare leaders in the U.S. can better prepare workers for future challenges. Continued research and testing will decide the long-term role of these technologies in improving pharmacy education and practice.
CAIAs in pharmacy education are used as innovative and scalable training solutions to address complex educational and practice demands, particularly supporting communication skills, human resource management, and HIV care training.
Common characteristics include scenario-based learning, immediate real-time automated feedback, interactive learning, and multiple interaction modalities such as text, audiovisual, and voice, mostly designed for single-user formats.
Evaluated outcomes include functionality, user experience, cost-benefit, user characteristics, and educational outcomes such as confidence, knowledge, and skills development among learners.
Most CAIAs utilize text-based interaction; some include audiovisual elements, one study combines text and voice, while others rely solely on text, predominantly in single-user formats.
CAIAs are largely in early adoption stages: three studies in feasibility/usability, two in effectiveness, and one in efficacy evaluation stage.
CAIA uptake remains low, with variable and poorly described learner interaction. Additional validation of their effectiveness and expansion to other healthcare disciplines are necessary.
The WHO digital health framework informed the development of an evaluation framework capturing key characteristics and outcome measures for CAIAs, enhancing structured design and assessment.
Eleven educational features and three educational outcome categories were incorporated into the evaluation framework to guide CAIA design and evaluation in pharmacy education.
CAIAs have shown potential in increasing learner confidence, knowledge, and communication skills, despite currently low adoption rates.
Further research is needed to validate CAIA effectiveness, expand their use beyond pharmacy to other healthcare fields, and test the proposed evaluation framework more broadly.
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