津巴布韦保险业采用人工智能和机器学习的挑战

Judith Moyo, Noreen Watyoka, F. Chari
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摘要

本研究旨在调查在津巴布韦保险行业采用人工智能和机器学习的挑战。本文选择技术-组织-环境(TOE)模型作为本研究的基础理论。本研究采用务实的研究理念,对20家保险公司进行了调查。对代表其保险公司的业务经理进行了问卷调查。通过访谈收集了12位运营经理的数据。使用NVivo version 16对数据进行主题分析。研究结果表明,津巴布韦保险部门采用人工智能受到资源短缺、缺乏专业知识和人工智能合规产品成本高的阻碍。这些研究人员建议资源分配、员工培训、文化变革和更新技术环境,以确保人工智能的有效采用。本研究将有助于知识体系,对保险从业人员和政策制定者具有重要意义,同时为未来的研究提供方向。
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Challenges in the Adoption of Artificial Intelligence and Machine Learning in Zimbabwe’s Insurance industry
This study sought to investigate the challenges in the adoption of AI and ML in the Zimbabwean insurance industry. The TechnologyOrganisation-Environment (TOE) model was selected as the base theory underpinning the study. The study adopted a pragmatic research philosophy and a census was carried out on twenty insurance companies. Questionnaires were administered on operations managers representing their insurance companies. Interviews were used to collect data from 12 operation managers. NVivo version 16 was used to analyse the data thematically. The study results show that adoption of AI by the insurance sector in Zimbabwe is hindered by shortage of resources, lack of expertise and high cost of AI compliant products. These researchers recommend resource allocation, training of employees, culture change, and updated technological environment to ensure effective adoption of AI. This study will contribute to the body of knowledge, be significant to insurance practitioners and policy makers whilst giving direction for future studies.
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