The impact of artificial intelligence on business models: a bibliometric-systematic literature review

Abstract

Purpose This study aims to conduct a bibliometric-Systematic Literature Review’ (B-SLR) to trace the impact of artificial intelligence (AI) on business models (BM). It explores the intellectual structure, key thematic clusters and the evolution of this emerging field, with the aim of identifying current trends and future research directions. Design/methodology/approach The analysis covers 87 journal articles retrieved from the Scopus database. It follows the guidelines of a multi-method literature review, combining a bibliometric analysis and a systematic literature review. Co-citation, co-occurrence and timeline analyses were performed to uncover intellectual foundations, map key research areas and track recent developments. Findings The study highlights the central role of AI in reshaping BM, particularly in areas such as customer engagement, innovation, sustainability, Industry 4.0 and digitalization. Recent developments emphasize AI’s applications in narrow fields, circular BM and the growing influence of generative AI. A framework of AI adoption in BM is developed, suggesting promising directions for future research. Research limitations/implications This study suggests that future research should explore AI’s role in BM more deeply by integrating interdisciplinary perspectives. It highlights the need for more empirical studies on AI-driven innovation and its long-term effects on business strategies, particularly in emerging areas such as generative AI and circular economy models. Practical implications This review provides managers with insights into how AI can drive BM innovation and highlights emerging areas of AI applications. It offers a roadmap for integrating AI technologies into BM to gain competitive advantages. Originality/value This study provides an up-to-date, comprehensive analysis of AI’s impact on BM, contributing to both academic literature and practical business strategies by synthesizing recent developments and suggesting future research directions.