Browsing by Author "Kunene, Thamsanqa Mxolisi"

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    The perceived impact of artificial intelligence on operations performance in the South African life insurance industry
    (University of the Witwatersrand, Johannesburg, 2022) Kunene, Thamsanqa Mxolisi; Appiah, Erasmus Kofi
    Organisations are increasingly implementing AI applications in their operations in order to stay competitive. The Covid-19 pandemic has further fuelled the implementations of AI technologies. However, do these applications improve the operation’s performance of an organisation? The study investigates how managers and employees that have implemented AI technologies within life insurance organisations perceive AI to have impacted their operations performance. Operations performance measures used by the study are cost, quality, speed, flexibility, and dependability. A qualitative methodology was undertaken by the study, using in-depth interviews that were made up of open-ended questions. The participants that contributed to the study were selected based on their profile and experience with AI technologies and in the life insurance industry. The findings of the study show that AI technologies generally improved operations performance. However, it must be noted that AI implementations come at a very high cost. Therefore, using cost savings as a sole use case driver is discouraged. Also, AI must not be implemented to improve inefficient business processes. Lastly, the quality of data to be used by the AI application is essential to the success of the project. In conclusion, managers and employees that have implemented and/or used AI technologies in the life insurance industry perceive AI to have improved operations performance of their organisations. An improved operations performance helps the organisation to stay competitive among its peers.