Human–Machine Interaction in Self-Checkout Systems: User Experience, Technical Challenges and Future Directions

Self-checkout (SCO) systems have become an integral part of modern retail, yet their increasing popularity has also revealed a number of technical and usability challenges that influence customer experience and technology acceptance. This paper investigates human–machine interaction in self-checkout systems based on a survey conducted among 419 young adults in Poland. The study combines quantitative and qualitative analyses to identify the most commonly reported technical difficulties, users’ attitudes toward current self-checkout systems, and their expectations regarding future technological developments. The results indicate that although self-checkout systems are generally perceived as intuitive, convenient, and time-saving, their broader acceptance is limited by recurring self-reported problems related to age verification, weighing scales, product recognition, and the need for employee intervention. Respondents consistently emphasized that future technological innovations should build upon reliable and user-centered existing systems by addressing current usability limitations before introducing entirely new functionalities. At the same time, they expressed a positive attitude toward AI-assisted solutions, including automated product recognition and intelligent age verification, provided that these technologies increase perceived reliability and preserve users’ sense of control. The findings highlight that successful technological innovation in self-checkout systems should be driven by human-centered design, with improvements in usability forming the foundation for the adoption of future AI-assisted solutions.