Abstract
This study explores barriers to AI adoption in automated organizational decision-making. Through qualitative interviews with 13 senior managers in South Africa, the study identified human social dynamics, restrictive regulations, creative work environments, lack of trust, dynamic business environments, loss of power, and ethical considerations. The study applied the adaptive structuration theory (AST) model to AI decision-making adoption, providing recommendations to overcome these barriers. The AST offers a deeper understanding of the dynamic interaction between technological and social dimensions.
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