The main objective of this study is to design and test a conceptual model explaining the effects of artificial intelligence (AI) on key dimensions of employees’ interpersonal behavior (including teamwork and organizational trust), considering the mediating role of perceived algorithmic fairness in companies listed on the Tehran Stock Exchange. In the era of digital transformation, understanding the implications of integrating AI into human resource management (HRM) processes for employees’ relationships and interactions in high‑risk and highly transparent environments (such as publicly listed firms) is essential.
This research is applied in purpose and employs a descriptive–survey methodology based on structural equation modeling (SEM). The statistical population consists of employees and middle managers of listed companies operating in the technology and financial sectors. Data were collected using a standardized questionnaire, and SmartPLS software was used to test the hypotheses.
The analysis results indicate that the impact of AI on employees’ interpersonal behavior is predominantly indirect and occurs through the mediating variable. Perceived algorithmic fairness functions as a full mediator for the effect of AI on teamwork and a partial mediator for the effect of AI on organizational trust. The strongest path coefficient pertains to the direct effect of perceived algorithmic fairness on organizational trust, suggesting that employees’ positive perceptions of transparent and fair AI‑driven processes constitute the most critical factor in maintaining their trust.
The proposed model highlights the vital role of employees’ perceptual dimensions in moderating the influence of emerging technologies. For a successful transition toward intelligent organizations, listed companies must focus on developing ethical policies and enhancing transparency in the deployment of AI systems to prevent the erosion of trust and collaboration within the workforce.