Artificial Intelligence-Based Methods for Business Processes: A Systematic Literature Review
Source abstract
Abstract
Companies are usually overloaded with data that they may not know how to take advantage of. On the other hand, artificial intelligence (AI) techniques are known to “keep learning” as the data increase. In this context, our research question emerges: what AI-based methods, in the literature, could be used to automatize business processes and support the decision-making processes of companies? To fill this gap, in this paper, we performed a review of the literature to identify these techniques. We ensured the usage of methods since they allowed reproducibility and extensions. We applied our search string in the Scopus and Web of Science databases and discovered 21 relevant papers pertaining to our question. In these papers, we identified methods that automated tasks and helped analysts make assertive decisions when designing, extending, or reengineering business processes. The authors applied diverse AI techniques, such as K-means, Bayesian networks, and swarm intelligence. Our analysis provides statistics about the techniques and problems being tackled and point to possible future directions.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Business Process Modeling and Analysis · Big Data and Business Intelligence · Data Quality and Management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Departamento de Administração, Faculdade de Administração e Direito da Universidade de Pernambuco, Campus Benfica, Universidade de Pernambuco, Pernambuco 50720-001, Brazil
Departamento de Engenharia da Computação, Escola Politécnica da Universidade de Pernambuco, Campus Benfica, Universidade de Pernambuco, Pernambuco 50720-001, Brazil
Funding
Fundação de Amparo à Ciência e Tecnologia de Pernambuco · Coordenação de Aperfeicoamento de Pessoal de Nível Superior
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