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Examining the Diffusion of Innovations from a Dynamic, Differential-Effects Perspective: A Longitudinal Study on AI Adoption Among Employees

  • Shan Xu
  • , Kerk F. Kee
  • , Wenbo Li
  • , Masahiro Yamamoto
  • , Rachel E. Riggs
  • Texas Tech University
  • SUNY Albany
  • University of North Florida

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

Abstract

This study extends the diffusion of innovations theory by considering the threat of technology and examining the adoption of artificial intelligence (AI) in the workplace over time from a dynamic, differential-effects perspective. Findings from a three-wave survey study reveal an association between the threat of AI (i.e., job security concerns) and increasingly negative attitudes toward AI adoption among employees over time. Relative advantage, compatibility, and observability correlated with more positive attitudes, whereas ease of use and trialability showed no significant association. In testing the differential effects on attitudes toward AI adoption among different groups of potential adopters, we found that trialability positively influenced attitudes only among employees who held a positive attitude previously. Observability and the threat of AI, however, were more influential among employees who held a negative attitude previously. Theoretical and practical implications were discussed.

Original languageEnglish
Pages (from-to)843-866
Number of pages24
JournalCommunication Research
Volume51
Issue number7
DOIs
StatePublished - Oct 2024

Keywords

  • AI
  • adoption
  • artificial intelligence
  • diffusion of innovations
  • dynamic
  • employment
  • innovation attributes
  • longitudinal
  • threat

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