TY - JOUR
T1 - The arcanum of artificial intelligence in enterprise applications: Toward a unified framework
AU - Herrmann, Heinz
PY - 2022/9
Y1 - 2022/9
N2 - Disagreement and confusion about artificial intelligence (AI) terminology impede researchers, innovators, and practitioners when developing and implementing enterprise applications. The prevailing ambiguities and use of buzzwords are exacerbated by media and vendor marketing hype. This study identifies several ambiguities within and across AI fields and subfields. Combining a systematic review with a sequential mixed-models design, a total of 26,143 publications were reviewed and mapped, making this the largest conceptual study in the AI field. A unified framework is proposed as an Euler diagram to bring about clarity through a "common language" for AI researchers, innovators, and practitioners.
AB - Disagreement and confusion about artificial intelligence (AI) terminology impede researchers, innovators, and practitioners when developing and implementing enterprise applications. The prevailing ambiguities and use of buzzwords are exacerbated by media and vendor marketing hype. This study identifies several ambiguities within and across AI fields and subfields. Combining a systematic review with a sequential mixed-models design, a total of 26,143 publications were reviewed and mapped, making this the largest conceptual study in the AI field. A unified framework is proposed as an Euler diagram to bring about clarity through a "common language" for AI researchers, innovators, and practitioners.
U2 - https://www.sciencedirect.com/science/article/pii/S0923474822000467
DO - https://www.sciencedirect.com/science/article/pii/S0923474822000467
M3 - Article
SN - 0923-4748
VL - 66
SP - 101716
JO - Journal of Engineering and Technology Management - JET-M
JF - Journal of Engineering and Technology Management - JET-M
IS - Oct-Dec 2022
ER -