@article{article_1792848, title={ANALYSIS OF ARTIFICIAL INTELLIGENCE READINESS PERFORMANCE OF EUROPEAN UNION COUNTRIES: AN APPLICATION USING THE LOPCOW-BASED GRA METHOD}, journal={Marmara Üniversitesi Avrupa Araştırmaları Enstitüsü Avrupa Araştırmaları Dergisi}, volume={33}, pages={23–51}, year={2025}, DOI={10.29228/mjes.465}, author={Altıntaş, Furkan Fahri}, keywords={Yapay zekâ (YZ), yapay zekâ hazırlık performansı, Avrupa Birliği (AB) ülkeleri, LOPCOW, LOPCOW tabanlı GRA.}, abstract={The activities and strategies of the European Union (EU), one of the world’s most significant economic actors, in the field of ArtificiaI Intelligence (AI) have the potential to influence the global economy and the AI policies of other countries. Therefore, analyzing the AI readiness performance of EU countries is considered crucial. In this study, the AI readiness performance of EU countries for the most recent year, 2023, was measured using the LOPCOW-based Grey Relational Analysis (GRA) Multi-Criteria Decision Making (MCDM) method, based on the Government AI Readiness Index (GAIRI) criteria values. According to the findings, the most critical GAIRI criterion for countries was identified as the government. Secondly, the top three countries with the highest AI readiness performance were found to be Finland, France, and Germany, while the bottom three were Croatia, Romania, and Greece, respectively. Additionally, the average AI readiness performance value for countries was measured, and it was assessed that EU countries with below-average performance need to improve their AI readiness to contribute to the global economy. Finally, sensitivity, comparison, and simulation analyses indicated that the AI readiness performance of EU countries under the GAIRI framework can be measured using the LOPCOW-based GRA method.}, number={1}, publisher={Marmara Üniversitesi}