Three Horizons of Technical Skills in Artificial Intelligence for the Sustainability of Insurance Companies

Julio César Acosta-Prado (), Carlos Guillermo Hernández-Cenzano, Carlos David Villalta-Herrera and Eloy Wilfredo Barahona-Silva
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Julio César Acosta-Prado: Department of Engineering, Pontifical Catholic University of Peru, Lima 15088, Peru
Carlos Guillermo Hernández-Cenzano: Department of Engineering, Pontifical Catholic University of Peru, Lima 15088, Peru
Carlos David Villalta-Herrera: Systemic Planning Research Group—PLANSYS, Pontifical Catholic University of Peru, Lima 15088, Peru
Eloy Wilfredo Barahona-Silva: Systemic Planning Research Group—PLANSYS, Pontifical Catholic University of Peru, Lima 15088, Peru

Administrative Sciences, 2024, vol. 14, issue 9, 1-18

Abstract: Insurance companies are experiencing unprecedented growth due to several emerging technology functionalities that have transformed the industry’s operations. Through the Three Horizons framework, this study explores the technical skills required to use artificial intelligence (AI) for the sustainability of insurance companies. Methodologically, it was carried out in two stages: First, defining the state-of-the-art, which included analysis of the current situation and studying technological surveillance. Second, technical skills and their strategic prevalence were identified for the design of each horizon. As a result, the adoption of AI in insurance companies allows them to transform their personal and data-intensive processes into engines of efficiency and knowledge, redefining the way companies in the sector offer their services. This study identifies the immediate benefits of AI in insurance companies. It provides a strategic framework for future innovation, emphasizing the importance of developing AI competencies to ensure long-term sustainability.

Keywords: three horizon framework; artificial intelligence; technical skills; insurance companies; sustainability (search for similar items in EconPapers)
JEL-codes: L M M0 M1 M10 M11 M12 M14 M15 M16 (search for similar items in EconPapers)
Date: 2024
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