The article addresses the problem of the insufficient empirical recognition of the determinants of trust in artificial intelligence (AI) algorithms in organizations operating under conditions of sustainable development. The aim of the study was to identify the factors shaping organizational trust in AI and to examine how perceived trustworthiness, transparency, and effectiveness of algorithms influence their acceptance in the work environment. The research was conducted using a quantitative survey-based approach among organizational employees, which enabled the analysis of relationships between key variables and the identification of factors that strengthen or limit trust. The results indicate that algorithmic transparency, the reliability of generated outcomes, and the perceived effectiveness of AI applications significantly foster trust, whereas concerns related to errors and the decision-making autonomy of systems constitute important barriers to acceptance. Based on the findings, a conceptual and exploratory model of trust in AI was proposed, which may be used to diagnose the level of technology acceptance and to support the responsible implementation of artificial intelligence-based solutions in organizations. The contribution of the article lies in integrating organizational and technological perspectives and in providing an empirical approach to trust in AI within the context of sustainable development.
Salwin et al. (Mon,) studied this question.