%0 Journal Article %1 TarafdarBeathRoss17itpro %A Tarafdar, Monideepa %A Beath, Cynthia M. %A Ross, Jeanne W. %D 2017 %J IT Professional %K 01841 ieee paper ai cognitive system enterprise business application data knowledge processing learn %N 4 %P 21--27 %R 10.1109/MITP.2017.3051321 %T Enterprise Cognitive Computing Applications: Opportunities and Challenges %V 19 %X Enterprise cognitive computing (ECC) applications are generating a great deal of excitement for organizations. However, they have yet to demonstrate a business impact on a large scale. An important reason for this is a failure to understand how such applications can contribute to a company's business objectives and the challenges associated with implementing them. In this article, the authors provide an overview of cognitive computing applications for the enterprise. In particular, they classify opportunities for developing ECC applications and describe challenges in implementing them. Their findings are based on a study of 51 ECC application initiatives across a broad range of industries in North America, Europe, and the Asia-Pacific region. Given the lack of systematic descriptions regarding what is possible from ECC, this article should be valuable to researchers and practitioners in unpacking the black box of cognitive computing.

@article{TarafdarBeathRoss17itpro, abstract = {Enterprise cognitive computing (ECC) applications are generating a great deal of excitement for organizations. However, they have yet to demonstrate a business impact on a large scale. An important reason for this is a failure to understand how such applications can contribute to a company's business objectives and the challenges associated with implementing them. In this article, the authors provide an overview of cognitive computing applications for the enterprise. In particular, they classify opportunities for developing ECC applications and describe challenges in implementing them. Their findings are based on a study of 51 ECC application initiatives across a broad range of industries in North America, Europe, and the Asia-Pacific region. Given the lack of systematic descriptions regarding what is possible from ECC, this article should be valuable to researchers and practitioners in unpacking the black box of cognitive computing.}, added-at = {2017-10-30T16:13:01.000+0100}, author = {Tarafdar, Monideepa and Beath, Cynthia M. and Ross, Jeanne W.}, biburl = {https://www.bibsonomy.org/bibtex/2bf5ecec7f8b2761bd103fa2de9db03c0/flint63}, doi = {10.1109/MITP.2017.3051321}, file = {IEEE Digital Library:2017/TarafdarBeathRoss17itpro.pdf:PDF}, groups = {public}, interhash = {5595bd3f5b965b9038d158cacee6c784}, intrahash = {bf5ecec7f8b2761bd103fa2de9db03c0}, issn = {1520-9202}, journal = {IT Professional}, keywords = {01841 ieee paper ai cognitive system enterprise business application data knowledge processing learn}, number = 4, pages = {21--27}, timestamp = {2018-04-16T11:54:12.000+0200}, title = {Enterprise Cognitive Computing Applications: Opportunities and Challenges}, username = {flint63}, volume = 19, year = 2017 }