Global experiences, intelligent technologies: the development of an AI-enabled customer experience (AICX) scale

Purpose This study introduces artificial intelligence–enabled customer experience (AICX) conceptualised as distinct, multidimensional form of customer experience arising from interactions with AI-enabled technologies and develops and validates a novel scale to measure the phenomenon. Design/methodology/approach The research comprises five studies and follows established scale development procedures. Study 1 generates and refines scale items; Study 2 purifies and validates the factor structure; Studies 3 and 4 establish nomological, discriminant and criterion validity with customer satisfaction and engagement; Study 5 tests cross-cultural validity across Western (UK/USA) and East Asian (Taiwan/South Korea) samples. Findings Findings reveal a reliable and valid 12-item, four-dimensional AICX scale comprising affiliation, affinity, amusement and advancement constructs. The scale demonstrates strong psychometric properties, including internal consistency, convergent and discriminant validity, and predictive validity, and significant predictor of customer satisfaction and engagement. Cross-cultural analysis supports configural, metric and partial scalar invariance, indicating the scale's applicability across national contexts. Research limitations/implications Findings are based on online panel data and a limited set of countries. Future research should extend validation across industries and cultural contexts. Originality/value By conceptualising AICX as a multidimensional phenomenon and providing a robust measurement tool, the research advances customer experience theory and enables rigorous empirical investigation of AI-driven service interactions across global contexts.