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How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops

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  • Sjödin, David
  • Parida, Vinit
  • Palmié, Maximilian
  • Wincent, Joakim

Abstract

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.

Suggested Citation

  • Sjödin, David & Parida, Vinit & Palmié, Maximilian & Wincent, Joakim, 2021. "How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops," Journal of Business Research, Elsevier, vol. 134(C), pages 574-587.
    • Handle: RePEc:eee:jbrese:v:134:y:2021:i:c:p:574-587
    DOI: 10.1016/j.jbusres.2021.05.009
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