From intelligent customer service perception to user positive behavioral intention: The mediating role of human–AI trust and the moderating effects of user technology cognition and risk perception

Purpose Against the backdrop of the swift intelligent transition of the world’s service sector, there remains a lingering gap between the pervasive application of intelligent customer service (ICS) and real user experience. Based on trust theory, this study develops an integrated Perception–Trust–Behavior framework to investigate how perceived functionality and interaction quality together influence users’ positive behavioral intention towards ICS, mediated by human–AI trust. The boundary conditions exerted by technology cognition and risk perception are also investigated. Methods Using survey data from 489 Chinese consumers and structural equation modeling, three key findings emerge. Findings (1) Human–AI trust is found to mediate the relationship between ICS perception and positive behavioral intention indirectly, as it serves as the main psychological conduit between experiential appraisal and relational commitment; (2) technology cognition negatively moderates the perception-trust relationship, where trust gains are weakened by an “expert scrutiny effect” among high-cognition users; (3) risk perception positively reinforces this pathway with a risk signal amplification effect greatly increasing trust formation in high-risk situations. Implications The results clarify how trust develops in ICS, offering both theoretical insights and practical guidance for firms seeking to adopt context-sensitive, user-tailored trust-building strategies—thus addressing the pervasive “hot technology, cold experience” paradox.