L'intelligence artificielle et secteur des services dans les pays de l'OCDE
DOI :
https://doi.org/10.18559/rielf.2026.1.4486Mots-clés :
secteur des services, intelligence artificielle, méthode GMM, OCDERésumé
Objectif : L ’ émergence de l ’ intelligence artificielle a profondément transformé le marché du travail, en particulier dans le secteur des services, où de nombreuses professions ont été redéfinies ou supprimées. Ce secteur se caractérise désormais par une concentration croissante de métiers nécessitant des compétences en intelligence artificielle. Cet article vise à analyser l ’ impact de l ’ intelligence artificielle sur l ’ emploi dans le secteur des services au sein des pays de l ’ Organisation de coopération et de développement économiques (OCDE).
Conception/méthodologie/approche : Cet article utilise la méthode des moments généralisés (GMM), en utilisant des données secondaires annuelles couvrant la période 2012–2024, dans 36 pays de l ’ OCDE, à l ’ aide du logiciel STATA 17.0.
Résultats : Les résultats indiquent un remplacement des emplois dans le secteur des services, où le résultat du modèle GMM montre que l ’ emploi dans le secteur des services diminue de 4,8% pour chaque point de l ’ indice d ’ adoption de l ’ IA. Par conséquent, il est essentiel de combler l ’ écart intersectoriel afin d ’ assurer une transition harmonieuse sur le marché du travail. Ce constat suggère un déplacement des emplois entre les professions et les secteurs.
Originalité/valeur : Cette étude propose une mesure inédite de l ’ IA construite à l ’ aide d ’ une analyse en composantes principales (ACP) à partir des brevets déposés par les résidents et les non-résidents dans les pays de l ’ OCDE. Les résultats révèlent un impact négatif de l ’ IA sur l ’ emploi dans le secteur des services, soulignant la nécessité de repenser les politiques du marché du travail et de mettre en oeuvre des stratégies ciblées de perfectionnement et de reconversion des compétences afin d ’ aider les travailleurs du secteur des services à s ’ adapter aux tendances émergentes de l ’ emploi.
JEL Classification
Econometrics (C01)
Estimation: General (C13)
Forecasting and Prediction Methods • Simulation Methods (C53)
Labor Force and Employment, Size, and Structure (J21)
Technological Change: Choices and Consequences • Diffusion Processes (O33)
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