Abstract
Artificial Intelligence is a disruptive technology developed during the 20th century, which has undergone an accelerated evolution, underpinning solutions to complex problems in the business world. Neural Networks, Machine Learning, or Deep Learning are concepts currently associated with terms such as digital marketing, decision making, industry 4.0 and business digital transformation. Interest in this technology will increase as the competitive advantages of the use of Artificial Intelligence by economic entities is realised. The aim of this research is to analyse the state-of-the-art research of Artificial Intelligence in business. To this end, a bibliometric analysis has been implement using the Web of Science and Scopus online databases. By using a fractional counting method, this paper identifies 11 clusters and the most frequent terms used in Artificial Intelligence research. The present study identifies the main trends in research on Artificial Intelligence in business and proposes future lines of inquiry.
Highlights
Journal of Business Economics and Management, 2021, 22(1): 98–117 routes, recalculating new routes based on unexpected events and maintaining contact with the client and the logistics service provider in a fluid and automatic way; It has an influence on after-sales services, analyzing the opinion of customers about products and services, to assess their level of satisfaction and possible failures or improvements that may apply to products/services (Plastino & Purdy, 2018)
From a technical point of view, and in accordance with the results of the research, it is reasonable to think of a future in which scientific works focus on some of the following aspects: Emergence of specific hardware for the implementation of Artificial intelligence (AI) solutions
The current supply of this hardware is concentrated in a few companies, such as Google, which has developed TensorFlow technology acceleration units (Tensor Processing Units or TPUs), or NVIDIA, incorporating circuitry (Tensor Cores) to accelerate the training processes of neural networks
Summary
AI already has a significant impact on network marketing processes and services, through the analysis of user behavior in networks and the creation of user profiles to which product and service offerings are oriented; It affects the production departments, managing maintenance in a predictive way, automating quality control and detecting anomalies in the production lines before problems occur; It influences the logistics processes, calculating efficient. AI has gone from, in the twentieth century, being a branch of knowledge in the field of computer science with limited application and restricted by the capabilities of the hardware of the time, to becoming a vital element for the development of industry and services of 21st century society
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