期刊
JOURNAL OF BUSINESS RESEARCH
卷 134, 期 -, 页码 574-587出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jbusres.2021.05.009
关键词
Artificial intelligence; Digital servitization; Digital transformation; Digitalization; Business model innovation; Platform
类别
This paper explores how manufacturing firms can scale AI in digital servitization, presenting three critical AI capabilities: data pipeline, algorithm development, and AI democratization. It suggests that firms need to innovate their business models by focusing on customer co-creation, data-driven delivery operations, and ecosystem integration to scale AI effectively.
Artificial intelligence (AI) is predicted to radically transform the ways manufacturing firms create, deliver, and capture value. However, many manufacturers struggle to successfully assimilate AI capabilities into their business models and operations at scale. In this paper, we explore how manufacturing firms can develop AI capabilities and innovate their business models to scale AI in digital servitization. We present empirical insights from a case study of six leading manufacturers engaged in AI. The findings reveal three sets of critical AI capabilities: data pipeline, algorithm development, and AI democratization. To scale these capabilities, firms need to innovate their business models by focusing on agile customer co-creation, data-driven delivery operations, and scalable ecosystem integration. We combine these insights into a co-evolutionary framework for scaling AI through business model innovation underscoring the mechanisms and feedback loops. We offer insights into how manufacturers can scale AI, with important implications for management.
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