Artificial intelligence and internet of things adoption in operations management: Barriers and benefits

• Autor(a) principal: Rocha,Isabela F.
• Data de Publicação: 2022
• Outros Autores: Kissimoto,Kumiko O.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: RAM. Revista de Administração Mackenzie
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712022000400202
• topic: digital technologies; digital transformation; operations management; artificial intelligence; internet of things

Abstract Purpose: Based on the context of digital transformation and the evolution of digital technologies, this research sought to understand how artificial intelligence (AI) and internet of things (IoT) collaborate to improve the efficiency of operations management (OM). Originality/value: Digital transformation and the use of new technologies, such as AI and IoT, have impacted the management of the companies’ operation. A preliminary survey carried out in the Web of Science (WoS) database, analyzing data through the VOSviewer bibliometric software, identified an important relationship between AI, IoT, and OM through industry 4.0 (i4.0), which has as one of its main objectives the improvement in OM. The results of this research bring a practical contribution to business managers, such as the identification of the main barriers and expected benefits when adopting AI and IoT in their operations. For researchers, this study differs from studies already published by conducting a systematic review of the literature that investigates the relationship of OM with technological tools, such as AI and IoT. Design/methodology/approach: A systematic review of the literature was carried out with the objective of analyzing all articles that brought some contribution to a better understanding of how AI and IoT collaborate to improve the efficiency of operations. Findings: The results demonstrated how AI and IoT were being incorporated into OM, identifying the main barriers of its use, as well as indications of research gaps that may lead to further investigations to advance on this topic.