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

  • Guangming Cao*
  • , Yanqing Duan
  • , John S. Edwards
  • , Yogesh K. Dwivedi
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

392 Scopus citations

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
DOIs
StatePublished - Aug 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 The Authors

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)

ASJC Scopus subject areas

  • General Engineering
  • Management of Technology and Innovation

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