Analysing the mediating relationship between using artificial intelligence and threats to professional identity
Tatyana Yu. Stuken, Dr. Sc. (Econ.), Dean of Economics, Psychology and Management
Faculty. Dostoevsky Omsk State University
Abstract
The article analyses employees’ assessments related to the consequences of using artificial intelligence (AI) in their workplaces. The paper highlights subjective risks that threaten the professional identity of employees, namely: changes in job functions, devaluation of human capital, and job loss. The formation of these risks relates to the experience of using AI in the workplace. The study tests two hypotheses regarding the formation of threats to an employee’s professional identity: the first one is that the threat of losing professional identity is more characteristic for employees who have no experience of using AI (the fear hypothesis); the second one links the threat of losing professional identity with experience in using AI (the awareness hypothesis). Based on empirical data from the 33rd wave of the RLMS-HSE, we analyse a model in which experience of interacting with AI in the workplace acts as a mediating factor determining this fear. The results of Bayesian mediation analysis confirm the awareness hypothesis. The use of AI in the workplace increases the threat to professional identity. Based on the results obtained, we conclude that it is feasible to revise strategies for adapting to digitalisation and that it is important to shift the focus to developing skills in employees that cannot be automated. In the business environment, communications focused on replacing labour with AI should be reoriented towards increasing employee productivity with the help of AI.
Keywords: digital transformation; labour substitution by artificial intelligence; utilising AI at work; human capital; professional identity
For citation: Stuken T. Yu. Analysing the mediating relationship between using artificial intelligence and threats to professional identity. Digital Models and Solutions. 2026. Vol. 5, no. 1, pp. 77–88. DOI: 10.29141/2949-477X-2026-5-1-5. EDN: RVYEKU.
