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Intuition or artificial intelligence? When do decision-makers rely on AI decision-aids for ill-structured problems

Author

Listed:
  • Vinod U. Vincent
  • Nishani Edirisinghe Vincent
  • Leon Prieto

Abstract

PurposeWith its superior analytical and decision-making capabilities, Artificial Intelligence (AI) is a valuable decision aid that enables organizational decision-makers to make effective and efficient decisions while reducing human errors. However, decision-makers continue to disproportionately rely on their intuition, especially when making decisions for ill-structured problems characterized by uncertainty and ambiguity. In this study, we assess the conditions in which decision-makers are willing to forego their intuition and rely on an AI decision aid for an ill-structured problem.Design/methodology/approachUsing a mixed-methods research design that included an experiment and an open-ended questionnaire, we assessed the conditions in which decision-makers are more likely to override their intuition and depend on an AI decision aid for an ill-structured decision.FindingsWe found that the decision-makers' reliance on the AI decision aid depended on two criteria: when the decision alternatives were similar rather than different, and when there was a considerable difference in the AI assessment of the decision alternatives. The qualitative analysis offered insights into the factors influencing participants' reliance on either their intuition or the AI decision aid.Originality/valueAI aversion is a significant issue for organizational development. The findings of this study increase our understanding of when and why decision-makers are more likely to rely on AI decision aids.

Suggested Citation

  • Vinod U. Vincent & Nishani Edirisinghe Vincent & Leon Prieto, 2025. "Intuition or artificial intelligence? When do decision-makers rely on AI decision-aids for ill-structured problems," American Journal of Business, Emerald Group Publishing Limited, vol. 40(4), pages 161-183, October.
  • Handle: RePEc:eme:ajbpps:ajb-01-2025-0014
    DOI: 10.1108/AJB-01-2025-0014
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