Weaving the future: AI-driven tacit knowledge capture and digital servitization in the Thai textile heritage industry

This study examines how artificial intelligence (AI) can capture the tacit knowledge of Thai artisan weavers while enabling sustainable digital servitization. The industry faces critical structural challenges, such as an aging artisan population and intergenerational knowledge gaps. This study employs an exploratory sequential mixed-methods design. Initial interviews with 25 master weavers revealed a central concern—"Fear of the Forgotten Pattern”— over cultural erasure, and a preference for technology that augments rather than replaces the automation of traditional craft. A subsequent quantitative analysis of 261 weavers using a structural model with Partial Least Squares Structural Equation Modeling (PLS-SEM) statistically validated these insights. The results indicate that the perceived utility of AI for knowledge capture significantly predicts the intention to adopt digital service models ( β = 0.621). This, in turn, strongly predicts positive relationships with perceived economic sustainability ( β = 0.589) and perceived cultural sustainability ( β = 0.645). Overall, this study contributes a validated model for human-centric digital transformation in cultural and creative industries, reframing AI as an epistemic partner that preserves legacy while ensuring a culturally authentic and innovative future.