Understanding Managers’ Attitudes and Behavioral Intentions towards Using Artificial Intelligence for Organizational Decision-Making

Guangming Cao*, Yanqing Duan, John Edwards, Yogesh Kumar Dwivedi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Article number102312
JournalTechnovation
Volume106
Early online date8 Jun 2021
DOIs
Publication statusE-pub ahead of print - 8 Jun 2021

Bibliographical note

© 2021 The Authors. This is an open access article under the CC BY-NC-ND license

Keywords

  • AI adoption
  • Artificial intelligence
  • Integrated AI acceptance-Avoidance model (IAAAM)
  • Organizational decision-making
  • Technology threat avoidance theory (TTAT)
  • Unified theory of acceptance and use of technology (UTAUT)

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