Artificial intelligence (AI) marketing technologies are reshaping customer engagement in service sectors, yet their performance within integrated digital ecosystems remains poorly understood. Existing research often examines AI tools in isolation, overlooking how the holistic quality of the virtual customer experience (VCE) shapes their impact on consumer decisions, particularly in intangible service contexts such as telecommunications. This study addresses this gap by investigating the influence of four AI technologies—chatbots, dynamic pricing, voice search, and visual search—on purchasing decisions, with VCE tested as a critical moderating mechanism. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) and survey data from 487 telecommunications customers in Saudi Arabia, the findings confirm significant positive direct effects for all four AI tools. Moreover, the VCE significantly amplifies these individual relationships and further strengthens their combined contribution to decision quality, enabling the model to explain 71.2% of the variance in purchasing decisions. The results indicate that competitive advantage in AI-enabled service markets depends not on deploying isolated technologies, but on orchestrating a coherent, high-quality virtual experience ecosystem. By integrating the Technology Acceptance Model (TAM) and Stimulus–Organism–Response (SOR) framework, this study advances the theoretical understanding of how AI and experience design jointly enhance digital decision-making. Practically, it underscores the need for managers to prioritize integrated VCE design to drive sustainable consumption and strengthen customer loyalty in increasingly digital service environments.

This study investigates the determinants of chatbot adoption intention in Jordan's civil status and passport department, with a particular focus on technology trust as a moderating variable. Drawing on the Technology Acceptance Model (TAM), we developed and tested hypotheses regarding chatbot adoption factors. The research employed a quantitative approach, collecting data from 687 valid respondents out of 743 distributed questionnaires. Analysis using Smart-PLS software revealed that most examined factors positively influenced adoption intentions, with one notable exception: ease of use showed no significant impact on user attitudes. The findings confirmed that positive attitudes toward chatbots significantly enhanced adoption intentions, while trust in technology strengthened this attitude-intention relationship. This study extends existing theoretical frameworks by providing empirical evidence from a Middle Eastern context, specifically in Jordan's public sector, offering valuable insights for both researchers and practitioners implementing chatbot solutions in public services. The results particularly emphasize how trust in technology shapes user acceptance in the Jordanian context, contributing new perspectives to the current understanding of chatbot adoption dynamics.