Industry 4.0 (I4.0) is a manufacturing paradigm revolutionising production by integrating advanced technologies, like AI, for automation and data integration. However, research in I4.0 overlooks human factors, crucial for designing systems that enhance well-being, trust, motivation, and performance. To address this, international bodies have introduced Industry 5.0, aiming to balance technological advancement with human welfare. To transition towards this vision, an understanding of current human-technology interaction is essential. Through a conceptual model aiming to understand the psychological experience of workers within their environment, we identified the studied human factors, their antecedents, consequences, and methodologies. Additionally, we explored how future research can adopt a human-centred approach in designing and implementing technology. Analysis of 67 articles showed the psychosocial dimension of human factors like AI trust, worker autonomy, motivation, and stress are underrepresented. We observed a significant disconnect between empirical and non-empirical studies in terms of theoretical frameworks, variable selection, data collection methods, and research designs. Our findings highlight the necessity for experimental, theory-driven research in human-AI interaction, using a multi-method approach including perceptual, observational, and psychophysiological measures. Lastly, we discuss the integration of these findings into managerial practice to foster workplaces that are technologically advanced yet remain empathetic to human needs.