Artificial intelligence in business management: A systematic thematic literature review of emerging applications, research gaps, and future directions

Artificial Intelligence (AI) has become a transformative force in contemporary business administration, enhancing strategic decision-making, operational efficiency, innovation, and organizational competitiveness. However, research on AI remains fragmented across business disciplines, limiting understanding of the field’s intellectual structure, dominant themes, and future directions. This study systematically synthesizes existing knowledge on AI applications in business administration, identifies major thematic areas, highlights research gaps, and proposes a comprehensive future research agenda. A Systematic Thematic Literature Review (STLR) was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Peer-reviewed articles published between 2015 and 2026 were retrieved from Scopus and Web of Science using predetermined inclusion and exclusion criteria. Thematic synthesis was applied to identify patterns, conceptual developments, and research trends. Eight major themes emerged: AI-driven decision-making, marketing and consumer analytics, human resource management, financial management, supply chain and operations management, ethical AI governance, human–AI collaboration, and strategic organizational transformation. The findings indicate that AI has evolved from an operational automation tool into a strategic organizational capability supporting digitalization, business performance, and sustainable competitive advantage. Key gaps concern cross-functional AI integration, Generative AI, Explainable AI, responsible governance, sustainability, SME adoption, and empirical evidence from developing economies and diverse industry contexts.