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

• Published in: Business horizons Vol. 63; no. 2; pp. 157 - 170
• Main Authors: Lee, In, Shin, Yong Jae
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.03.2020
• Subjects: Artificial intelligence; Big data; Chatbot; Deep learning; Innovation capability; Machine learning; Neural networks; Resources and capabilities; Deep learning; Neural networks; Machine learning; Chatbot; Resources and capabilities; Big data; Innovation capability; Artificial intelligence
• ISSN: 0007-6813; 1873-6068
• DOI: 10.1016/j.bushor.2019.10.005

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.