Transparency and Accountability in the Use of Artificial Intelligence: Analysis of the Attitudes of the Organization’s Employees

Abstract

The article examines organizational readiness for responsible artificial intelligence by analysing employees’ attitudes toward key dimensions of transparency and accountability in algorithmic decision-making. The study was designed to explore how workers perceive human responsibility for AI-generated outcomes, the need for disclosing the use of algorithms in organizational processes, the role of ethical training, and the importance of algorithmic audit mechanisms. A quantitative survey conducted in 2025 on a sample of 325 respondents was complemented with a multiple correspondence analysis, which made it possible to identify underlying structures in the distribution of responses and to capture differences in the intensity and certainty of opinions. The findings reveal a clear acceptance of fundamental ethical norms such as human oversight and transparency, contrasted with less decisive attitudes toward more advanced organizational practices including systematic ethical training and audit procedures. These results indicate that while employees support foundational principles of responsible AI, organizations still face challenges in implementing procedural and technical mechanisms that ensure full accountability. The study offers practical insights for managers and policymakers by identifying areas where competence-building, communication and institutional frameworks require strengthening. Its originality lies in combining attitudinal data with MCA to provide a nuanced picture of how transparency and accountability are understood by employees in everyday organizational contexts, contributing to the broader debate on ethical and trustworthy AI deployment.