Which enterprises are more competitive in AI-field from the perspective of patentometrics?

Purpose The pivotal role of artificial intelligence (AI) technology in industrial upgrading has necessitated an understanding of its evolving competitive landscape and technological trends. This paper proposes a patent data analysis framework based on fine-grained knowledge units, which is applied to provide a landscape analysis of enterprises’ technological competitive advantage in the AI field. Design/methodology/approach AI patent data collected from the Derwent Innovation Index (DII) database. The competitive patterns of the AI industry are investigated through an analysis of patent applications, regional distributions and a social network analysis of the International Patent Classification (IPC) and Derwent Manual Code (MC). Findings The study found that China, Japan and the United States are leading in AI technologies in terms of technological prowess and market potential. Emerging sectors include intelligent education, biological identification, intelligence servers, intelligent terminals, big data analysis and information security. Companies like IBM, Panasonic, Microsoft and Google demonstrate unique strategic orientations, with IBM notable for having the highest number of patents and citations. The analysis indicates a growing, concentrated and multi-path development profile for AI patenting, with interorganizational technical flows primarily. Research limitations/implications The research is limited by the scope of patent data and the methodologies employed, which may not capture the full spectrum of AI technological advancements and competitive dynamics. Future studies should consider incorporating additional data sources for a more comprehensive analysis. Based on the particularity of AI technology, elements like open resources should be paid special attention. Practical implications The study provides actionable strategic recommendations for AI industry stakeholders, emphasizing the importance of focused technological development, international collaboration and strategically designed patent portfolio management. These insights can help stakeholders navigate the complexities of the AI industry and adapt their strategies to fit evolving technological trends. Originality/value Most previous studies on AI patent data analysis have used a macro (whole) perspective at the country level. However, this study narrows its focus to research from a micro perspective, that is, at the enterprise level. This paper studies the technological competition pattern of enterprises in the AI industry from the perspectives of competitive environment and competitive strength.