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AI Literacy for the top management: An upper echelons perspective on corporate AI orientation and implementation ability

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  • Pinski, Marc
  • Hofmann, Thomas
  • Benlian, Alexander

Abstract

We draw on upper echelons theory to examine whether the AI literacy of a firm’s top management team (i.e., TMT AI literacy) has an effect on two firm characteristics paramount for value generation with AI—a firm’s AI orientation, enabling it to identify AI value potentials, and a firm’s AI implementation ability, empowering it to realize these value potentials. Building on the notion that TMT effects are contingent upon firm contexts, we consider the moderating influence of a firm’s type (i.e., startups vs. incumbents). To investigate these relationships, we leverage observational literacy data of 6986 executives from a professional social network (LinkedIn.com) and firm data from 10-K statements. Our findings indicate that TMT AI literacy positively affects AI orientation as well as AI implementation ability and that AI orientation mediates the effect of TMT AI literacy on AI implementation ability. Further, we show that the effect of TMT AI literacy on AI implementation ability is stronger in startups than in incumbent firms. We contribute to upper echelons literature by introducing AI literacy as a skill-oriented perspective on TMTs, which complements prior role-oriented TMT research, and by detailing AI literacy’s role for the upper echelons-based mechanism that explains value generation with AI.

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  • Pinski, Marc & Hofmann, Thomas & Benlian, Alexander, 2025. "AI Literacy for the top management: An upper echelons perspective on corporate AI orientation and implementation ability," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 154096, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:154096
    DOI: 10.1007/s12525-024-00707-1
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/154096/
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    References listed on IDEAS

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    1. Toutaoui, Jonas & Benlian, Alexander & Hess, Thomas, 2022. "Managing paradoxes in bi‐modal information technology functions: A multi‐case study," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 135837, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Toutaoui, Jonas & Benlian, Alexander & Hess, Thomas, 2022. "Managing paradoxes in bi-modal information technology functions: A multi-case study," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 132709, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Alexander Benlian & Martin Wiener & W. Alec Cram & Hanna Krasnova & Alexander Maedche & Mareike Möhlmann & Jan Recker & Ulrich Remus, 2022. "Algorithmic Management," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(6), pages 825-839, December.
    4. Reis, Carolina & Ruivo, Pedro & Oliveira, Tiago & Faroleiro, Paulo, 2020. "Assessing the drivers of machine learning business value," Journal of Business Research, Elsevier, vol. 117(C), pages 232-243.
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