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Understanding knowledge hiding under technological turbulence caused by artificial intelligence and robotics
- Source :
- Journal of Knowledge Management. 26:1476-1491
- Publication Year :
- 2021
- Publisher :
- Emerald, 2021.
-
Abstract
- Purpose Artificial intelligence (AI) will be performing 52% of the tasks in companies by 2025. The increasing adoption of AI is generating technological turbulence in the business environment. Previous studies have also shown that employees are aware of the high risk of losing their jobs when being replaced by AI. The risk of employees engaging in opportunistic behaviors, such as knowledge hiding, is thus fairly high. Therefore, the aim of this paper is to analyze the mediating effect of employee’s AI awareness on the relationship between technological turbulence generated by AI and the three types of knowledge hiding: evasive hiding, playing dumb and rationalized hiding. Design/methodology/approach Structural equations by the partial least squares method were used to test the proposed research model. Findings The most interesting finding is that employee’s AI and robotics awareness fulfills almost all mediating functions in the relationship between technological turbulence generated by AI and the three types of knowledge hiding. Originality/value The results show that knowledge hiding in the digital age is first and foremost a strategy by employees to sabotage and induce failure in process automation, to reduce the risk of being replaced in the workplace by AI. This study indicates that employees are willing to hide knowledge in all possible ways when perception that AI is a threat to their job increases. In other words, technological turbulence generated by AI and employee’s AI awareness are the two great new triggers of knowledge hiding in the digital age.
- Subjects :
- Transaction cost
Descriptive knowledge
Knowledge management
business.industry
Computer science
Strategy and Management
media_common.quotation_subject
Digital transformation
Robotics
Work in process
Automation
Test (assessment)
Management of Technology and Innovation
Perception
Artificial intelligence
business
media_common
Subjects
Details
- ISSN :
- 13673270
- Volume :
- 26
- Database :
- OpenAIRE
- Journal :
- Journal of Knowledge Management
- Accession number :
- edsair.doi...........22dfa8a77a575a18793c20bb7bf1878e