Mapping Artificial Intelligence Research in Strategic Management: A Bibliometric Analysis and Future Research Agenda

Artificial intelligence (AI) is increasingly embedded in strategic decision-making, competitive positioning, innovation management, organizational learning, and governance, yet the literature remains fragmented across management, information systems, innovation, and technology-management fields. This study provides a focused bibliometric review of AI research in strategic management. Scopus was used as the primary database, and the query "artificial intelligence" AND "strategic management" was applied to titles, abstracts, and keywords, with restrictions to Business, Management and Accounting, Article and Review document types, and English-language publications. From 126 retrieved records, relevance screening excluded 82 records, leaving 44 publications for analysis. The study examines annual trends, citation patterns, keyword co-occurrence, country distribution, science maps, TCCM synthesis, and a WoS/SSCI sensitivity analysis. Results show slow development before 2018 and marked acceleration after 2023, with 2026 treated as an incomplete year. Themes are shifting from decision support and strategic planning toward generative AI, innovation management, sustainability, organizational capabilities, and governance. By combining bibliometric mapping, TCCM, and cross-database sensitivity analysis, this study offers a knowledge-structure map and future research agenda.

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Publication Details

Journal
International Review of Management and Marketing
Published
2026-11-01
DOI
https://doi.org/10.32479/irmm.24625
Primary Topic
Artificial Intelligence Applications
Type
article
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article

Mapping Artificial Intelligence Research in Strategic Management: A Bibliometric Analysis and Future Research Agenda

Dzhumabek Dzhailov, Fei Kang, Shanning Fu
5 links
International Review of Management and Marketing
Artificial Intelligence Applications
article

Mapping Artificial Intelligence Research in Strategic Management: A Bibliometric Analysis and Future Research Agenda

Dzhumabek Dzhailov, Fei Kang, Shanning Fu
article en

Abstract

Artificial intelligence (AI) is increasingly embedded in strategic decision-making, competitive positioning, innovation management, organizational learning, and governance, yet the literature remains fragmented across management, information systems, innovation, and technology-management fields. This study provides a focused bibliometric review of AI research in strategic management. Scopus was used as the primary database, and the query "artificial intelligence" AND "strategic management" was applied to titles, abstracts, and keywords, with restrictions to Business, Management and Accounting, Article and Review document types, and English-language publications. From 126 retrieved records, relevance screening excluded 82 records, leaving 44 publications for analysis. The study examines annual trends, citation patterns, keyword co-occurrence, country distribution, science maps, TCCM synthesis, and a WoS/SSCI sensitivity analysis. Results show slow development before 2018 and marked acceleration after 2023, with 2026 treated as an incomplete year. Themes are shifting from decision support and strategic planning toward generative AI, innovation management, sustainability, organizational capabilities, and governance. By combining bibliometric mapping, TCCM, and cross-database sensitivity analysis, this study offers a knowledge-structure map and future research agenda.

International Review of Management and MarketingVol. 17(1)
National Academy of Sciences of the Republic of Kyrgyzstan (KG), Kyrgyz National University (KG)
Openalex Percentile: Top 14%
Artificial Intelligence Applications
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