Аннотация
This study aims to provide a comprehensive analysis of the impact of digital transformation on labor productivity in industrial enterprises. In the context of globalization and technological progress, the digitalization of industrial production has become a crucial factor in economic growth. Digital technologies–automation, artificial intelligence, big data analytics, cloud computing, and the industrial Internet of Things (IoT) are key tools for improving labor productivity. These technologies not only enhance production efficiency but also strengthen the competitiveness of enterprises, expanding their opportunities to enter global markets. The study examines international experiences in assessing the impact of digital transformation on labor productivity. Reforms implemented under Germany's "Industry 4.0" initiative, South Korea's digital strategies, and Singapore's "Smart City" program are analyzed, highlighting their effects on the industrial sector. In these countries, the adoption of digital technologies is considered a critical factor in increasing labor productivity. Additionally, the research explores the current state of digital transformation in Kazakhstan's industrial enterprises, identifying key barriers and opportunities. The main challenges of industrial digitalization in Kazakhstan are related to infrastructure limitations, a shortage of qualified personnel, and the low readiness of enterprises to adopt new technologies. Addressing these issues requires enhanced government support, the development of digital infrastructure, and the strengthening of enterprises' innovation potential. The findings of this study indicate that the effective implementation of digital transformation in Kazakhstan will become a vital component of national innovation development, positively impacting labor productivity and sustainable economic growth. The widespread adoption of digital technologies will enable industrial enterprises to optimize production processes, expand into new markets, and improve their competitiveness.