01741nas a2200229   4500008004100000022001400041245008900055210006900144260004200213300001000255490000700265520103800272653002801310653002301338653002601361653000701387653002001394653002301414100001901437700002501456856003001481       2020                        eng d  a1927-032100aThe Effect of Machine Learning on Knowledge-Intensive R&D in the Technology Industry0 aEffect of Machine Learning on KnowledgeIntensive RD in the Techn  aOttawabTalent First Networkc03/2020  a88-980 v103 aThe impact of such current state-of-the-art technology as machine learning (ML) on organizational knowledge integration is indisputable. This paper synergizes investigations of knowledge integration and ML in technologically advanced and innovative companies, in order to elucidate the value of these approaches to organizational performance. The analyses are based on the premise that, to fully benefit from the latest technological advances, entity interpretation is essential to fully define what has been learned. Findings yielded by a single case study involving one technological firm indicate that tacit and explicit knowledge integration can occur simultaneously using ML, when a data analysis method is applied to transcribe spoken words. Although the main contribution of this study stems from the greater understanding of the applicability of machine learning in organizational contexts, general recommendations for use of this analytical method to facilitate integration of tacit and explicit knowledge are also provided.10aartificial intelligence10aexplicit knowledge10aknowledge integration10aML10atacit knowledge10atechnological firm1 aViberg, Daniel1 aEslami, Mohammad, H.  utimreview.ca/article/1340