In today’s dynamic service industry, organisations face the challenge of effectively integrating artificial intelligence (AI) and service-oriented human resource systems (SHPWS) to optimise frontline employee (FLE) service delivery and organisational performance. These elements are often implemented in silos, neglecting their systemic impact. This disconnect, coupled with the potential unforeseen consequences of FLEs’ perceptions of these integrated systems, poses a significant challenge. Socio-technical systems theory advocates for a holistic approach to organisational design, recognising the interdependence of human and technological components. However, evidence linking this approach to improved organisational performance is limited. At the individual level, attributional theory offers a valuable lens for explaining how FLEs’ perceptions of workplace initiatives shape their attitudes and behaviours. Yet, it is often oversimplified, and narrowly applied to HR-related attribution triggers. This study examines data from multiple sources in 50 hospitality settings across multiple countries at two time points. By modelling the interaction between intended AI actions and enacted SHPWS, it explores how FLEs perceive and react to these systems. At the individual level, FLE attributions (n=603) play a key role in shaping well-being and service performance. At the organisational level (n=50), findings highlight a complex relationship between enacted SHPWS and AI systems. Moderate SHPWS implementation generates positive synergies, while excessive reliance on technology can have adverse effects. Furthermore, the study identifies how differentiation strategy influences the relationship between FLEs’ attributions of service systems and their well-being. This research highlights the potential of SHPWS – AI system integration to enhance FLE well-being and organisational performance. By examining the complex interactions between employees, customers, and organisations at the service frontlines, this study proposes a novel framework linking FLE attributions of service systems to performance outcomes. It offers actionable insights for organisations aiming to effectively balance human and technological elements in their service delivery.