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

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.