Conditions for the Use of Artificial Intelligence in Customer Service for Enhanced Efficiency: A Case Study Within Johnson & Johnson Medtech Switzerland

This Master Thesis investigates the integration of artificial intelligence (AI) technologies within the customer service operations at Johnson & Johnson Medtech Switzerland. The Medtech industry is uniquely positioned to leverage AI to enhance operational efficiencies and customer service quality in an era of rapid technological developments.

Cassata, Sabrina, 2024

Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Pilorget, Lionel
Keywords Artificial Intelligence, Customer Service, Medtech, Predictive Analytics, Generative AI, Com-puter Vision, Natural Language Processing, Operational Efficiency, Artificial Intelligence Im-plementation
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This thesis revolves around the main research question: “How can AI technologies, particularly predictive analytics, transform customer service processes to increase efficiency within the Medtech industry?” Central to this research is the inquiry about four specific AI technologies, namely predictive analytics, generative AI, computer vision, and natural language processing.
Employing a mixed-methods approach that synthesizes literature reviews, expert interviews, and surveys, this study not only identifies but also evaluates the practical applications of these AI technologies. The findings underscore AI's significant role in optimizing customer service workflows, improving data management, and refining customer interactions. Furthermore, the thesis offers strategic recommendations for deploying AI solutions that are in harmony with organizational objectives and tackle prevalent challenges such as technology integration and change management.
Ultimately, this thesis delineates AI's transformative potential in Medtech customer services and provides Johnson & Johnson Medtech Switzerland with a strategic roadmap to leverage AI for enhanced operational efficiency and customer satisfaction. This research also under-scores the importance of a foundational digital infrastructure and skilled oversight for success-fully implementing AI, suggesting broader applicability and directions for future research across the organization.
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Cassata, Sabrina
Betreuende Dozierende
Pilorget, Lionel
Publikationsjahr
2024
Sprache der Arbeit
Englisch
Vertraulichkeit
öffentlich
Studiengang
Business Information Systems (Master)
Standort Studiengang
Olten
Keywords
Artificial Intelligence, Customer Service, Medtech, Predictive Analytics, Generative AI, Com-puter Vision, Natural Language Processing, Operational Efficiency, Artificial Intelligence Im-plementation