Harnessing tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence Tacit knowledge is particularly valuable in product engineering. Experiences reside in minds of employees and are not systematically documented but could have a significant influence on sustainable product engineering. Existing approaches do not offer sufficient support for harnessing technical tacit knowledge regarding sustainable product engineering. In this paper a three-step method is presented: The method contains knowledge acquisition, requirements extraction und requirements validation for quality assurance. Acquisition is performed by support artifacts like interview guidelines. Extraction is supported by Artificial Intelligence, converting statements into requirements. These requirements are validated using a specific questionnaire. The developed approach is applied in a funded project of the European Union (EU) with automotive industry partners. The method supports product engineers to collect tacit knowledge from experienced employees, transform unsystematic knowledge into standardized technical requirements and validate them. Application of this method enables creation of validated requirements that can be applied throughout the company and are not exclusively dependent on a single employee. 1 229-238 229-238 Universitätsbibliothek