How can AI-powered business intelligence systems help veterinary practices implement personalized preventive care strategies while improving client satisfaction and revenue streams?

This thesis explores the integration of Artificial Intelligence (AI) and Business Intelligence (BI) systems in veterinary medicine, with a particular focus on how these technologies support preventive care, enhance client satisfaction, and optimize revenue streams. While AI is already transforming human healthcare through predictive analytics, diagnostic support, and personalized treatment plans, its adoption in veterinary medicine is still developing—especially in smaller markets such as Iceland. By reviewing recent academic literature and conducting interviews with veterinary professionals in Iceland, this study examines both the practical benefits and the challenges of AI and BI implementation. Key findings reveal that AI-powered tools can aid in early disease detection, streamline workflow, and improve clinical decision-making. However, barriers such as limited data quality, lack of staff training, and concerns over cost and ethical regulation remain significant. The research also highlights differences between the U.S. and European approaches to AI adoption, providing comparative insights for Icelandic practices. The study concludes that with responsible implementation, supported by education and regulation, AI and BI systems have the potential to significantly enhance the quality, efficiency, and sustainability of veterinary services.

Author dc:creator

• Sara Miller 1989-

Contributors dc:contributor

• Háskólinn á Bifröst

• Viðskiptafræði
• Gervigreind
• Viðskiptagreind

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/1946/50676

OAI identifier oai:identifier

oai:skemman.is:1946/50676