Electronic Theses and Dissertations (Masters/MBA)

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Author: search.filters.author.Mdingi, YangaSubject: search.filters.subject.AI adoption

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    Adoption of custom artificial intelligence models in South African small and medium-sized enterprises
    (University of the Witwatersrand, Johannesburg, 2023) Mdingi, Yanga; Lee, Gregory
    This study quantitatively investigates the potential adoption of custom AI models in South African SMEs using the Technology-Organization-Environment (TOE) framework. The adoption of AI in organizations is influenced by technological, organizational, and environmental elements, which can be examined using the TOE framework to understand the complexities of AI adoption. This research is guided by a post-positivist philosophical perspective to addresses the question: What factors impact the adoption of custom AI models in South African SMEs? The study employed a quantitative research design and survey methodology to collect data from South African SMEs. Participants were selected through a snowball sampling method, and data was gathered using a self-administered online questionnaire based on TOE model constructs, with each item assessed using a five-point Likert scale to capture participant opinions and attitudes. Statistical analysis, including Pearson correlation and hierarchical regression, revealed significant positive relationships between factors such as top management support, technological competence, competitive pressure, and external support, and the adoption of custom AI models. While perceived compatibility does not have a direct significant effect on AI adoption, the study revealed that it moderates the influence of top management support and technological competence on custom AI adoption. Practical recommendations of this study include prioritizing executive education, developing leadership training programs, recruiting and retaining technologically competent individuals, investing in employee training programs, leveraging external support from technology vendors and partners, recognizing the strategic importance of AI in competitive industries, and balancing efforts on perceived compatibility and management support. The findings provide actionable recommendations for enhancing AI adoption in South African SMEs, helping them overcome adoption challenges and improve competitiveness and sustainability in the local and global markets