Electronic Theses and Dissertations (Masters/MBA)

Permanent URI for this collectionhttps://hdl.handle.net/10539/37942

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    Artificial Intelligence-driven transformation of risk management function in the South African Telecommunications Industry
    (2022) Ramatar, Nitesh
    Current Artificial Intelligence (AI) solutions focus on improving business operational processes and specific applications within the risk management fraternity. AI enables organisations to accelerate processes rapidly. However, this fast pace introduces new risk exposures that require proactive risk management. Therefore, this study explored whether AI should be utilised within the risk function of a telecommunications company, to make the function proactive. The research adopted an exploratory approach that involved conducting face-to-face interviews with risk management professionals within the telecommunications environment. The respondents’ feedback was consolidated to identify and analyse findings. Findings noted that risk functions should adopt AI to help them transition from a reactive to a proactive function. However, key challenges, such as budget constraints, poor stakeholder buy-in, and limited access to AI skills and appropriate use cases, prevent risk functions from adopting AI. Establishing change management initiatives is recommended to create a culture that can overcome these challenges.