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Bases de connaissances des entreprises de Défense et capacités d’absorption des technologies de l’Intelligence Artificielle (IA) : Outils de modélisation et études de cas

Author

Listed:
  • Pierre Barbaroux

    (CReA - Centre de Recherche de l'École de l'air - Armée de l'air et de l'espace)

  • Didier Lebert

    (UEA - Unité d'Économie Appliquée - ENSTA Paris - École Nationale Supérieure de Techniques Avancées - IP Paris - Institut Polytechnique de Paris, CRG I3 - Centre de Recherche en Gestion I3 - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

Abstract

Cet article examine les fondements de la capacité d'absorption de trois grandes entreprises de Défense confrontées au défi de l'intégration des technologies de l'Intelligence Artificielle (IA) dans leurs processus de R&D. Nous utilisons des données de brevets afin de modéliser leurs bases de connaissances, d'étudier comment elles sont organisées et structurées, et d'explorer les relations qu'elles entretiennent avec les technologies de l'IA. Ce faisant, nous montrons comment les entreprises développent des capacités d'absorption des technologies IA singulières qui reflètent leurs domaines de compétences techniques et leur positionnement concurrentiel et conditionnent, en retour, leurs politiques de R&D et d'innovation.

Suggested Citation

  • Pierre Barbaroux & Didier Lebert, 2026. "Bases de connaissances des entreprises de Défense et capacités d’absorption des technologies de l’Intelligence Artificielle (IA) : Outils de modélisation et études de cas," Post-Print halshs-05645839, HAL.
    • Handle: RePEc:hal:journl:halshs-05645839
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