Strategic AI Orientation and Technological Innovation: Evidence From Managerial Insights and Panel Data

ABSTRACT Artificial intelligence (AI) is disrupting innovation. However, our understanding of firm‐level consequences remains limited. While firms are starting to develop a strategic AI orientation (i.e., goals and strategic directions), we neither know how firms establish a strategic AI orientation nor whether it suffices to increase firms' technological innovation. We explore these questions in two studies. In Study I, we conduct 42 interviews with AI managers in large firms. Using the attention‐based view to structure the qualitative insights, we build deductive hypotheses on the relationship between AI orientation and technological innovation. Study II tests our hypotheses quantitatively, using natural language processing to develop a text‐based measure of firms' strategic AI orientation. Applying this measure to S&P 500 firms between 2012 and 2021, we find that strategic AI orientation relates positively to firms' technological innovation, also across technology domains. CEOs' IT‐related education strengthens this link. These insights contribute to AI‐innovation research. First, we validate and refine the construct strategic AI orientation and its mechanism that links it to technological innovation. Second, we establish a positive AI‐innovation relationship from a strategic perspective, enhancing the external validity of research in this domain. Overall, this article offers a starting point for strategic AI research.

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Publication Details

Journal
Journal of Product Innovation Management
Published
2025-08-14
DOI
https://doi.org/10.1111/jpim.70001
Citations
1
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
2.11

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Strategic AI Orientation and Technological Innovation: Evidence From Managerial Insights and Panel Data

Stephan Nüesch, Christopher Albert Sabel, A. Eicke
1 citations
Journal of Product Innovation Management
Impact of AI and Big Data on Business and Society
2.11
article

Strategic AI Orientation and Technological Innovation: Evidence From Managerial Insights and Panel Data

Stephan Nüesch, Christopher Albert Sabel, A. Eicke
article en
1 citations

Abstract

ABSTRACT Artificial intelligence (AI) is disrupting innovation. However, our understanding of firm‐level consequences remains limited. While firms are starting to develop a strategic AI orientation (i.e., goals and strategic directions), we neither know how firms establish a strategic AI orientation nor whether it suffices to increase firms' technological innovation. We explore these questions in two studies. In Study I, we conduct 42 interviews with AI managers in large firms. Using the attention‐based view to structure the qualitative insights, we build deductive hypotheses on the relationship between AI orientation and technological innovation. Study II tests our hypotheses quantitatively, using natural language processing to develop a text‐based measure of firms' strategic AI orientation. Applying this measure to S&P 500 firms between 2012 and 2021, we find that strategic AI orientation relates positively to firms' technological innovation, also across technology domains. CEOs' IT‐related education strengthens this link. These insights contribute to AI‐innovation research. First, we validate and refine the construct strategic AI orientation and its mechanism that links it to technological innovation. Second, we establish a positive AI‐innovation relationship from a strategic perspective, enhancing the external validity of research in this domain. Overall, this article offers a starting point for strategic AI research.

Journal of Product Innovation ManagementVol. 43(2)
University of Fribourg (CH), Ludwig-Maximilians-Universität München (DE), Erasmus University Rotterdam (NL)
Ludwig-Maximilians-Universität München
Openalex Percentile: Top 11%
Impact of AI and Big Data on Business and Society
2.11
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Strategic AI Orientation and Technological Innovation: Evidence From Managerial Insights and Panel Data — Stephan Nüesch, Christopher Albert Sabel, et al. · Journal of Product Innovation Management (2025) | TGRS Research Map | TGRS