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Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making

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  • Cao, Guangming
  • Duan, Yanqing
  • Edwards, John S.
  • Dwivedi, Yogesh K.

Abstract

While using artificial intelligence (AI) could improve organizational decision-making, it also creates challenges associated with the “dark side” of AI. However, there is a lack of research on managers' attitudes and intentions to use AI for decision making. To address this gap, we develop an integrated AI acceptance-avoidance model (IAAAM) to consider both the positive and negative factors that collectively influence managers' attitudes and behavioral intentions towards using AI. The research model is tested through a large-scale questionnaire survey of 269 UK business managers. Our findings suggest that IAAAM provides a more comprehensive model for explaining and predicting managers' attitudes and behavioral intentions towards using AI. Our research contributes conceptually and empirically to the emerging literature on using AI for organizational decision-making. Further, regarding the practical implications of using AI for organizational decision-making, we highlight the importance of developing favorable facilitating conditions, having an effective mechanism to alleviate managers’ personal concerns, and having a balanced consideration of both the benefits and the dark side associated with using AI.

Suggested Citation

  • Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    • Handle: RePEc:eee:techno:v:106:y:2021:i:c:s0166497221000936
    DOI: 10.1016/j.technovation.2021.102312
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    7. Jung-Chieh Lee & Yuyin Tang & SiQi Jiang, 2023. "Understanding continuance intention of artificial intelligence (AI)-enabled mobile banking applications: an extension of AI characteristics to an expectation confirmation model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    8. Stroh, Tim & Mention, Anne-Laure & Duff, Cameron, 2023. "The impact of evolved psychological mechanisms on innovation and adoption: A systematic literature review," Technovation, Elsevier, vol. 125(C).
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    12. Akter, Shahriar & Hossain, Md Afnan & Sajib, Shahriar & Sultana, Saida & Rahman, Mahfuzur & Vrontis, Demetris & McCarthy, Grace, 2023. "A framework for AI-powered service innovation capability: Review and agenda for future research," Technovation, Elsevier, vol. 125(C).
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    14. Philippe Funk, 2022. "Artificial Intelligence And Cybersecurity Implications For Business Management," Economy & Business Journal, International Scientific Publications, Bulgaria, vol. 16(1), pages 252-261.
    15. Dicuonzo, Grazia & Donofrio, Francesca & Fusco, Antonio & Shini, Matilda, 2023. "Healthcare system: Moving forward with artificial intelligence," Technovation, Elsevier, vol. 120(C).
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