Machine learning for enterprises: Applications, algorithm selection, and challenges

In Lee and Yong Jae Shin

Business Horizons, 2020, vol. 63, issue 2, 157-170

Abstract: Machine learning holds great promise for lowering product and service costs, speeding up business processes, and serving customers better. It is recognized as one of the most important application areas in this era of unprecedented technological development, and its adoption is gaining momentum across almost all industries. In view of this, we offer a brief discussion of categories of machine learning and then present three types of machine-learning usage at enterprises. We then discuss the trade-off between the accuracy and interpretability of machine-learning algorithms, a crucial consideration in selecting the right algorithm for the task at hand. We next outline three cases of machine-learning development in financial services. Finally, we discuss challenges all managers must confront in deploying machine-learning applications.

Keywords: Machine learning; Artificial intelligence; Deep learning; Big data; Neural networks; Chatbot; Innovation capability; Resources and capabilities (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (32)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:bushor:v:63:y:2020:i:2:p:157-170

DOI: 10.1016/j.bushor.2019.10.005

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