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Rise of Artificial Intelligence Capabilities in Innovation Management: A Bibliometric Analysis

Year: 2025

Type: article

Abstract: The rapid advancement of artificial intelligence (AI) is fundamentally reshaping how organisations manage innovation, sustain competitiveness, and respond to dynamic market environments. As AI capabilities continue to evolve, understanding their implications for innovation management has become increasingly critical for organisations seeking long-term value creation and sustainable development. Despite a growing body of research on AI-driven innovation, existing studies are largely fragmented and focus on specific applications, offering limited holistic insight into the broader evolution and future trajectory of AI capabilities within innovation management. To address this gap, this study aims to provide a comprehensive analysis of past, current, and emerging trends in AI capabilities and innovation management. Using a systematic literature network analysis (SLNA) approach, the study integrates a systematic literature review (SLR) and bibliometric analysis based on Scopus-indexed publications. The SLR follows a structured three-step process comprising study scoping, database selection, and defined selection and evaluation criteria, while bibliometric techniques are employed to examine research performance and intellectual linkages through performance analysis and science-mapping methods. The findings identify key publication trends, influential journals, leading publications, and dominant country contributions, with sustainability-oriented research emerging as a central theme and China identified as the leading contributor to scholarly output in this domain. By synthesising the intellectual structure and evolution of the field, this study offers actionable insights for researchers, practitioners, and policymakers, supporting informed decision-making on how AI capabilities can be effectively leveraged to foster innovation, enhance organisational competitiveness, and promote sustainable innovation ecosystems.

Source: International Journal of Academic Research in Business and Social Sciences

DOI: 10.6007/ijarbss/v15-i12/27150

Authors: Al Harbi Mohammed Marshad, Razli Ramli, Almi Mahmod

Institution: University of Technology Malaysia

Language: English

Topic: Artificial Intelligence Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W7117127276