Which Industrial Sectors Are Affected by Artificial Intelligence? A Bibliometric Analysis of Trends and Perspectives

Lorena Espina-Romero (), José Gregorio Noroño Sánchez, Humberto Gutiérrez Hurtado, Helga Dworaczek Conde, Yessenia Solier Castro, Luz Emérita Cervera Cajo and Jose Rio Corredoira
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Lorena Espina-Romero: Escuela de Postgrado, Universidad San Ignacio de Loyola, Lima 15024, Peru
José Gregorio Noroño Sánchez: Facultad de Derecho, Universidad del Sinú “Elías Bechara Zainúm”, Monteria 230001, Colombia
Humberto Gutiérrez Hurtado: Escuela de Postgrado, Universidad San Ignacio de Loyola, Lima 15024, Peru
Helga Dworaczek Conde: Programa Maestría en Administración—MBA, Universidad Santo Tomás, Bogota 110231, Colombia
Yessenia Solier Castro: Escuela de Posgrado, Universidad César Vallejo, Lima 15314, Peru
Luz Emérita Cervera Cajo: Escuela de Posgrado, Universidad César Vallejo, Lima 15314, Peru
Jose Rio Corredoira: Escuela de Negocios, Universidad Internacional SEK, Quito 170134, Ecuador

Sustainability, 2023, vol. 15, issue 16, 1-18

Abstract: In recent times, artificial intelligence (AI) has been generating a significant impact in various industry sectors, which implies that companies must be ready to adjust to this promising start and progress in the direction of sustainability. The objective of this paper was to analyze the industrial sectors impacted by artificial intelligence during the period 2018–2022. The methodology consisted of applying a quantitative and bibliometric approach to a collection of 164 manuscripts indexed in Scopus with the help of statistical packages such as RStudio version 4.3.0, VOSviewer version 1.6.19, and Microsoft Excel 365. The results indicate that artificial intelligence is having a growing impact in sectors such as technology, finance, healthcare, the environment, and construction. Geographically, the most impacted sectors are in Europe and Asia, while the least impacted are in the Americas, Africa, and Oceania. It is proposed to conduct future research using AI in power quality (PQ), energy storage systems (ESSs) and hydrogen fuel cell (HFC) systems to contribute, firstly, in the transition to a more sustainable economy, followed by a decrease in dependence on fossil fuels. This research contributes to existing knowledge and paves the way for future exploration of qualitative aspects and emerging trends in the field of artificial intelligence influence in industrial sectors.

Keywords: artificial intelligence; industrial sectors; machine learning algorithms; healthcare; sustainability; economic inequality; transportation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:16:p:12176-:d:1213601

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