Consumer Perception of AI Chatbots in Pharmaceutical Customer Support Services

This study explores consumer perceptions of AI chatbots implemented in pharmaceutical customer support services. As the healthcare industry integrates artificial intelligence (AI) into its communication channels, understanding how consumers respond to and interact with these technologies is essential. The research assesses attitudes toward chatbot efficiency, reliability, and trustworthiness, while identifying factors that drive satisfaction and acceptance. A mixed-methods approach was used, combining quantitative survey data with qualitative insights. Statistical analysis reveals significant associations between perceived ease of use, response accuracy, and overall satisfaction. The findings suggest that while consumers appreciate the convenience of AI-powered support, concerns regarding empathy and error handling persist. This paper discusses these implications and recommends strategies for enhancing chatbot design to better meet consumer expectations in the pharmaceutical sector.

Authors

Publication Details

Journal
International Journal of Research in all Subjects in Multi Languages
Published
2025-01-01
DOI
https://doi.org/10.63345/ijrsml.v13.i4.5
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Consumer Perception of AI Chatbots in Pharmaceutical Customer Support Services

Niharika Singh
International Journal of Research in all Subjects in Multi Languages
AI in Service Interactions
article

Consumer Perception of AI Chatbots in Pharmaceutical Customer Support Services

Niharika Singh
article en

Abstract

This study explores consumer perceptions of AI chatbots implemented in pharmaceutical customer support services. As the healthcare industry integrates artificial intelligence (AI) into its communication channels, understanding how consumers respond to and interact with these technologies is essential. The research assesses attitudes toward chatbot efficiency, reliability, and trustworthiness, while identifying factors that drive satisfaction and acceptance. A mixed-methods approach was used, combining quantitative survey data with qualitative insights. Statistical analysis reveals significant associations between perceived ease of use, response accuracy, and overall satisfaction. The findings suggest that while consumers appreciate the convenience of AI-powered support, concerns regarding empathy and error handling persist. This paper discusses these implications and recommends strategies for enhancing chatbot design to better meet consumer expectations in the pharmaceutical sector.

International Journal of Research in all Subjects in Multi LanguagesVol. 14(4)
Openalex Percentile: Top 97%
AI in Service Interactions
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