MEASURING NATIONAL ARTIFICIAL INTELLIGENCE CAPACITY: A HOLISTIC APPROACH BASED ON HUMAN CAPITAL SPECIALIZATION

Authors : Fethi Aslan

Pages : 65-91

Doi:10.14514/beykozad.1552437

View : 20 | Download : 87

Publication Date : 2025-12-17

Article Type : Research Paper

Abstract :The transformative impact of artificial intelligence has made the need to acquire necessary skills for technology adoption and adaptation even more critical. This situation has highlighted the need for developing criteria, metrics, and methodologies to measure advancements in the field of artificial intelligence. The primary objective of this research is to determine the national level of specialization in the field of artificial intelligence. To achieve this goal, human capital elements such as knowledge base, skills, and sectoral experiences have been comprehensively examined. The research was conducted in three stages. In the first stage, a comprehensive conceptual framework was developed to examine the specialization level of human capital and related factors. This framework forms the theoretical foundation of the study. In the second stage, an original model was developed to measure the specialization level of human capital in the field of artificial intelligence. The AHP-Gauss method, a hybrid approach, was used in developing this model. In the final stage of the research, the developed model was used to analyze and comparatively evaluate the specialization level of human capital in AI across the countries included in the study scope. This stage enabled the empirical measurement of national artificial intelligence competencies and the establishment of a cross-country comparative assessment. The research findings reveal that the United States, the United Kingdom, India, Germany, and Canada are in leading positions in terms of human capital specialization levels in the field of artificial intelligence. The study\\\'s results emphasize the necessity of clarifying the strategic approach for developing human capital in the artificial intelligence domain and shed light on areas that require intensified focus in this context. These findings provide critically important data for the formulation of national artificial intelligence policies and the design of human capital development strategies.
Keywords : Yapay zeka yönetimi, Teknolojik değişimin yönetimi, Beşeri sermaye, Uzmanlaşma, AHP-Gauss

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