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L'IA Générative et l'Évaluation des Performances : Vers de Nouvelles Perspectives Organisationnelles

Author

Listed:
  • Christine Marsal

    (MRM-SI - Montpellier Research in Management - Systèmes d’Information - MRM - Montpellier Research in Management - UPVD - Université de Perpignan Via Domitia - UM - Université de Montpellier)

Abstract

L'implantation des intelligences artificielles génératives (IAG) soulève d'importantes attentes en matière de productivité organisationnelle. Cet article examine comment les IAG transforment le système d'évaluation des performances à travers le prisme de la théorie de l'architecture organisationnelle. L'étude s'appuie sur une méthodologie qualitative exploratoire combinant 5 entretiens semi-directifs et 30 questionnaires auprès de participants issus de 35 organisations. Les résultats révèlent que les IAG permettent une collecte massive et amplifiée d'indicateurs de performance tout en introduisant de nouvelles asymétries d'information. Le système de codécision humain-IAG induit des pratiques d'ajustements permanents et un déplacement des asymétries d'information entre parties prenantes. Cette recherche identifie les enjeux, opportunités et limites d'un système d'évaluation des performances en mode IAG, offrant des implications théoriques et managériales pour le pilotage organisationnel.

Suggested Citation

  • Christine Marsal, 2026. "L'IA Générative et l'Évaluation des Performances : Vers de Nouvelles Perspectives Organisationnelles," Post-Print hal-05789327, HAL.
    • Handle: RePEc:hal:journl:hal-05789327
    Note: View the original document on HAL open archive server: https://hal.science/hal-05789327v1
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