Impact of human and AI-agent services on customer learning, immersion and loyalty: the role of interactivity

Purpose This study aims to examine the influence of human-agent service (HAS) and artificial intelligence-agent service (AIAS) on customer learning (CLR), customer immersive experience (CIE) and customer loyalty (CLY) within online service interactions. Additionally, the study investigates the moderating role of perceived interactivity (PI) and the mediating effect of CIE in translating CLR into loyalty. Design/methodology/approach Study 1 employed a cross-sectional online survey conducted among 421 Indian online consumers using a non-probability sampling method. Participants who had prior interactions with both human and artificial intelligence (AI) service agents were included, and partial least squares structural equation modeling using SmartPLS 4.0 was applied for hypothesis testing. Study 2 utilized a controlled experimental design (N = 221) to examine the causal effect of AI service interactivity (low- vs high-interactivity conditions) on customer outcomes. The experiment was conducted using a between-subject design, and the results were analyzed using Hayes' PROCESS macro for mediation and moderation testing. Findings Study 1 results reveal that HAS and AIAS significantly impact CLR, which subsequently enhances CIE, leading to improved CLY. AIAS facilitates learning through automation and efficiency, whereas HAS fosters learning through personalization and empathy. The study confirms that CIE mediates the relationship between CLR and CLY, reinforcing the role of immersive engagement in building CLY. Additionally, PI moderates the relationships between HAS, AIAS and CLR, indicating that higher interactivity enhances CLR. Study 2 further demonstrates that increasing AI service interactivity positively influences CLR and CIE but does not have a direct impact on loyalty. Instead, learning and immersive experiences mediate the effect of AI interactivity on CLY intentions, emphasizing the importance of engagement and cognitive processing in AI-driven interactions. Practical implications Service providers should integrate human and AI-powered interactions strategically to enhance CLR and foster loyalty. Human agents should emphasize emotional engagement, while AI services should focus on interactivity and personalization. Businesses should adopt hybrid service models that maximize customer satisfaction, engagement and long-term loyalty in digital service environments. Originality/value This study bridges the gap between human-agent and AI-agent service research by integrating service-dominant logic. It highlights the distinct yet complementary roles of AI and human agents in driving CLR and CIE, with PI playing a crucial moderating role. The findings contribute new insights into AI-human collaboration in digital service environments, offering empirical validation of AI interactivity effects on customer engagement and loyalty formation.