Transforming Customer Journey Mapping with AI: From Static Pathways to Dynamic Orchestration

Abstract

This study examines how artificial intelligence is transforming customer journey mapping from static diagrams into dynamic orchestration across omnichannel environments. It adopts a systematic literature review of peer reviewed journal articles on artificial intelligence enabled journeys, customer experience, process mining, and journey orchestration. The synthesis reveals a clear shift from linear paths toward data driven systems that use contextual signals to personalise content, timing, and channel choice in real time. Studies highlight the growing role of chatbots, voice based assistants, recommender systems, and process mining techniques in reshaping touchpoints and visualising actual paths, but also show that these applications are often implemented in organisational silos. The review conceptualises artificial intelligence enabled customer journey mapping as an integrated capability that spans data infrastructure, analytical models, experience design, and governance. It concludes that alignment between journey representations and decision engines is required to achieve continuous, cross channel orchestration. The article also outlines future research directions on governance and performance outcomes.