Personnel Attitudes toward the Implementation of AI Solutions: A Pilot Study in the Transport Sector

Abstract

This article is devoted to analyzing the attitude of personnel in a transport enterprise towards the implementation of artificial intelligence (AI) for monitoring operator states. Drawing on the diffusion of innovations, technology acceptance and change management frameworks, it hypothesises that acceptance is shaped not only by technical features but also by psychological, socio cultural and communicative factors.The empirical foundation includes two sequentially connected stages: prototype testing in a simulation environment and field trials during real operations.The method involved semi-structured interviews with 20 employees (purposeful selection by work experience and age), followed by thematic and frequency analysis; to compare subjective “before/after” assessments, a nonparametric test of differences was applied. The findings show that the acceptance of an AI solution is determined not only by technical parameters but also by psychological, sociocultural, and communicative factors: perceptions of “observability” and control, algorithmic transparency, ergonomics, and staff participation in refinement.Based on the data, managerial mechanisms for reducing resistance are proposed: extended communication and explainability, user involvement in iterative design, targeted training, and a structured feedback protocol. Thus, an empirically grounded model of guided AI implementation in high-responsibility organizations is proposed, relevant for the practices of state and municipal governance.