The impact of artificial intelligence on business performance: a bibliometric analysis of publication trends
The integration of artificial intelligence (AI) is revolutionizing business operations by enhancing performance and creating new growth opportunities. AI optimizes operational efficiency, supports strategic decision-making, and enables disruptive innovations. This study aims to explore publication...
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| Format: | Article |
| Language: | English |
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Moroccan Association for Applied Science and Innovation
2025-02-01
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| Series: | Moroccan Journal of Quantitative and Qualitative Research |
| Subjects: | |
| Online Access: | https://revues.imist.ma/index.php/MJQR/article/view/53210 |
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| _version_ | 1823864926155833344 |
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| author | Rachid ZIKY Hicham BAHIDA Ahmed ABRIANE |
| author_facet | Rachid ZIKY Hicham BAHIDA Ahmed ABRIANE |
| author_sort | Rachid ZIKY |
| collection | DOAJ |
| description |
The integration of artificial intelligence (AI) is revolutionizing business operations by enhancing performance and creating new growth opportunities. AI optimizes operational efficiency, supports strategic decision-making, and enables disruptive innovations. This study aims to explore publication trends and quantitatively assess the existing literature on AI's impact on business performance. The central research question investigates how AI influences business performance and examines research dynamics and academic collaborations in this field. Employing a systematic quantitative literature review (SQLR) complemented by bibliometric analysis using VOSviewer software, the study utilized the Scopus database. Inclusion criteria filtered 447 relevant documents from an initial 3192 identified, covering the period from 2014 to 2023. The findings indicate a significant increase in publications on AI and business performance during this period. Bibliometric analysis identified the most influential authors and institutions, highlighting predominant keywords such as "big data," "automation," and "predictive analytics." Results underscore the importance of deep learning and performance optimization. Limitations include the reliance on the Scopus database and the restricted analysis period. This study provides a clear view of research trends and major contributions in AI applied to business, with recommendations to extend future research to other databases for a more comprehensive perspective.
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| format | Article |
| id | doaj-art-c25034717d984a3eaf241b5dfa5f92dc |
| institution | Kabale University |
| issn | 2665-8623 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Moroccan Association for Applied Science and Innovation |
| record_format | Article |
| series | Moroccan Journal of Quantitative and Qualitative Research |
| spelling | doaj-art-c25034717d984a3eaf241b5dfa5f92dc2025-02-08T16:06:02ZengMoroccan Association for Applied Science and InnovationMoroccan Journal of Quantitative and Qualitative Research2665-86232025-02-017110.48379/IMIST.PRSM/mjqr-v7i1.53210The impact of artificial intelligence on business performance: a bibliometric analysis of publication trendsRachid ZIKY0Hicham BAHIDAAhmed ABRIANEFSJES Agadir The integration of artificial intelligence (AI) is revolutionizing business operations by enhancing performance and creating new growth opportunities. AI optimizes operational efficiency, supports strategic decision-making, and enables disruptive innovations. This study aims to explore publication trends and quantitatively assess the existing literature on AI's impact on business performance. The central research question investigates how AI influences business performance and examines research dynamics and academic collaborations in this field. Employing a systematic quantitative literature review (SQLR) complemented by bibliometric analysis using VOSviewer software, the study utilized the Scopus database. Inclusion criteria filtered 447 relevant documents from an initial 3192 identified, covering the period from 2014 to 2023. The findings indicate a significant increase in publications on AI and business performance during this period. Bibliometric analysis identified the most influential authors and institutions, highlighting predominant keywords such as "big data," "automation," and "predictive analytics." Results underscore the importance of deep learning and performance optimization. Limitations include the reliance on the Scopus database and the restricted analysis period. This study provides a clear view of research trends and major contributions in AI applied to business, with recommendations to extend future research to other databases for a more comprehensive perspective. https://revues.imist.ma/index.php/MJQR/article/view/53210Artificial intelligenceBusiness performanceBibliometric analysisSystematic review |
| spellingShingle | Rachid ZIKY Hicham BAHIDA Ahmed ABRIANE The impact of artificial intelligence on business performance: a bibliometric analysis of publication trends Moroccan Journal of Quantitative and Qualitative Research Artificial intelligence Business performance Bibliometric analysis Systematic review |
| title | The impact of artificial intelligence on business performance: a bibliometric analysis of publication trends |
| title_full | The impact of artificial intelligence on business performance: a bibliometric analysis of publication trends |
| title_fullStr | The impact of artificial intelligence on business performance: a bibliometric analysis of publication trends |
| title_full_unstemmed | The impact of artificial intelligence on business performance: a bibliometric analysis of publication trends |
| title_short | The impact of artificial intelligence on business performance: a bibliometric analysis of publication trends |
| title_sort | impact of artificial intelligence on business performance a bibliometric analysis of publication trends |
| topic | Artificial intelligence Business performance Bibliometric analysis Systematic review |
| url | https://revues.imist.ma/index.php/MJQR/article/view/53210 |
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