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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Lorena Espina-Romero & José Gregorio Noroño Sánchez & Humberto Gutiérrez Hurtado & Helga Dworaczek Conde & Yessenia Solier Castro & Luz Emérita Cervera Cajo & Jose Rio Corredoira, 2023. "Which Industrial Sectors Are Affected by Artificial Intelligence? A Bibliometric Analysis of Trends and Perspectives," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12176-:d:1213601
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    Cited by:

    1. Lorena Espina-Romero & Doile Ríos Parra & José Gregorio Noroño-Sánchez & Gloria Rojas-Cangahuala & Luz Emerita Cervera Cajo & Pedro Alfonso Velásquez-Tapullima, 2024. "Navigating Digital Transformation: Current Trends in Digital Competencies for Open Innovation in Organizations," Sustainability, MDPI, vol. 16(5), pages 1-19, March.
    2. Vasilescu Cristina & Gheorghe Militaru, 2025. "The Impact of AI on Service Industries: A Bibliometric Study of Current Research Trends," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 3594-3608.
    3. Álvaro Gómez-Barroso & Iban Vicente Makazaga & Ekaitz Zulueta, 2024. "Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies," Energies, MDPI, vol. 18(1), pages 1-32, December.
    4. Svetozar D. Jankovic & Dejan M. Curovic, 2023. "Strategic Integration of Artificial Intelligence for Sustainable Businesses: Implications for Data Management and Human User Engagement in the Digital Era," Sustainability, MDPI, vol. 15(21), pages 1-19, October.
    5. Zoren N. Inowe, 2025. "ChatGPT on STEM 12 Students’ Perception, Motivation, Engagement and Understanding Graphs in Kinematics: An Exploration," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(7), pages 2283-2314, July.
    6. Adriana AnaMaria Davidescu & Marina-Diana Agafiței & Mihai Gheorghe & Vasile Alecsandru Strat, 2025. "A Machine Learning and Econometric Framework for Credibility-Aware AI Adoption Measurement and Macroeconomic Impact Assessment in the Energy Sector," Mathematics, MDPI, vol. 13(19), pages 1-31, September.

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