Analysis of artificial intelligence in business process automation in enterprises: a systematic review of the scientific literature

Gomez Maguiña A.J.; Sierra-Liñan F. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2024) · DOI: 10.18687/leird2024.1.1.288

Resumen

The objective of this study is to analyze how the use of artificial intelligence (AI) allows the automation of business processes in companies through a systematic review of the literature in recent years. The PRISMA methodology was used for the review, and an analysis of 174 articles was performed, obtaining 80 relevant articles, published and indexed in ScienceDirect (36), IEEE Xplore (26), Scielo (9), Scopus (8), ProQuest (1). Among the main trends are: Predictive Marketing (12), followed by Chatbots (10), Customer Tracking with AI (10), Voice Assistant (8), Deep Learning (5), Predictive Analytics (5), Industry 4.0 (4), Neural Networks (4) and finally Sales Tracking with AI (3). In addition, it ranks and answers questions such as the areas where artificial intelligence (AI) is applied for business process automation, having Sales Management (27%), Inventory Management (23%), Purchasing Management (19%), Financial Management (19%) and Human Resources (12%). India is the country that contributes with the highest scientific production on process automation with artificial intelligence (AI), representing 26% of the scientific production, followed by Australia (5%), China (5%) and the United States (5%). These results show that the production of scientific articles on artificial intelligence in the automation of business processes has experienced significant growth, which demonstrates the enormous scientific effort made in recent years.

Instituciones: Universidad Privada del Norte