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Research on Engineering Knowledge Management (EKM) has identified challenges with the systematic source of engineering knowledge for the design process optimisation. In this context, Knowledge-Based Engineering (KBE) is acknowledged as a key area within the EKM field and designated by the research community as a potential solution to carry out the effective capture and reuse of expert knowledge. However, papers on KBE for knowledge sourcing are not abundant in the literature and they are also dispersed. From this perspective, this research is an effort to further consolidate the learning gained on industrial practice on how engineering knowledge can be effectively sourced. This is achieved by realising a research survey, where using the resulting insights KBE practice reaching aerospace engineering offices shall be more efficiently delivered through fast and accurate knowledge extraction and encoding into usable methods and tools. The research findings provided by literature survey confirmed the existence of a research gap on knowledge sourcing; and more precisely they underlined the need for an extended KBE development process which integrates Artificial Intelligence (AI) tools and expert intervention to systematically manage the knowledge (using the KM methods and tools) efficiently captured and modelled (employing AI algorithms and expert involvement). Therefore, this paper concludes that there is a need for further research on the knowledge sourcing KBE aspect and presents the integration of KBE systems and AI implementations as a potential solution to develop the extended KBE development process requested by the industry. [ABSTRACT FROM AUTHOR]