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The diffusion of new technologies is crucial for the realization of socialand economic returns to innovation. Tracking and mapping technology diffusionis, however, typically limited by the extent to which we can observe technologyadoption. This study uses website texts to train a multilingual language modelensemble to map technology diffusion for the case of 3D printing. The studyidentifies relevant actors and their roles in the diffusion process. Theresults show that besides manufacturers, service provider, retailers, andinformation providers play an important role. The geographic distribution ofadoption intensity suggests that regional 3D-printing intensity is driven byexperienced lead users and the presence of technical universities. The overalladoption intensity varies by sector and firm size. These patterns indicate thatthe approach of using webAI provides a useful and novel tool for technologymapping which adds to existing measures based on patents or survey data.

Technology Mapping Using WebAI: The Case of 3D Printing