Artificial intelligence and the transformation of the labor market: Pedagogical challenges in training specialists

Abstract

This study aims to examine the impact of artificial intelligence (AI) on the transformation of the global labor market and to identify the pedagogical challenges in preparing specialists for effective performance in the digital economy. The research employs theoretical analysis, a comparative review of educational programs, and content analysis of national and international policy documents to capture current trends and gaps in workforce preparation. Findings. The results indicate a growing demand for specialists with interdisciplinary thinking, digital literacy, adaptability, and lifelong learning competencies. Yet, existing educational systems often lack sufficient flexibility and innovative capacity to meet these emerging requirements. Conclusions. Higher education institutions play a critical role in revising curricula, integrating AI-related content, and applying innovative pedagogical strategies. A shift toward competency-based, interdisciplinary, and technology-integrated education is essential to close the gap between traditional approaches and the needs of an AI-driven economy. Practical implications. The findings provide guidance for curriculum developers, policymakers, and academic institutions seeking to align educational practices with labor market demands. By implementing these recommendations, stakeholders can enhance the readiness of future professionals to thrive in rapidly changing digital environments.