Abstract
Artificial intelligence (AI) is emerging as a technology at the center of many political, economic, and societal debates. This paper formulates a new AI patent search strategy and applies this to provide a landscape analysis of AI innovation dynamics and technology evolution. The paper uses patent analyses, network analyses, and source path link count algorithms to examine AI spatial and temporal trends, cooperation features, cross-organization knowledge flow and technological routes. Results indicate a growing yet concentrated, non-collaborative and multi-path development and protection profile for AI patenting, with cross-organization knowledge flows based mainly on interorganizational knowledge citation links.
Highlights
Artificial intelligence (AI) involves the creation of machines or agents that seek to simulate human rationality [1,2,3]
Some researchers have adopted AI patent search strategies based on designated patent classification codes including the International Patent Classification (IPC) [22, 23]
While we summarily report on patent grants, noting where there are major differences compared with applications, our analysis uses patent applications which are useful for detailed consideration of topical technological trends [30]
Summary
Artificial intelligence (AI) involves the creation of machines or agents that seek to simulate human rationality [1,2,3]. AI may use machine learning, neural networks, deep learning, natural language processing, and other information technologies to imitate or augment human capabilities, through logical calculation or through cognitively modelling human consciousness [4, 5]. There is an expectation that AI will be a key driver of future economic development [7]. Bundled with other information and automation technologies, AI is a key enabler of what is seen as a rapidly evolving digital transformation phenomenon that is disrupting and challenging multiple aspects of business and society and driving organizational transformation and strategic change [9,10,11].
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