Development of the robotics industry of Kazakhstan and global trends: problems and solutions

The development of the robotics industry in Kazakhstan is an essential factor in the country’s industrial modernization and economic growth. However, Kazakhstan lags behind global leaders in robot adoption, automation density, and domestic robotics manufacturing. This study examines the challenges, trends, and solutions for robotics development in Kazakhstan, drawing comparisons with global benchmarks. A regression analysis was conducted to assess the impact of robot density, R&D investment, AI adoption, labor displacement, and STEM education on industrial productivity. The results indicate that robot density and AI investments significantly boost productivity, but Kazakhstan’s low STEM workforce and weak policy incentives limit automation growth. Additionally, automation-related labor displacement poses risks, necessitating comprehensive workforce reskilling programs. Key recommendations include increasing robotics R&D funding to at least 1% of GDP, providing tax incentives for automation investments, strengthening STEM education, and aligning robotics policies with global best practices. Kazakhstan must also attract foreign robotics firms, establish a legal framework for AI and robotics, and develop a local robotics manufacturing ecosystem. Future research should explore the long-term labor market effects of automation, cost-benefit analyses of robotics investments, AI-driven industrial automation, and infrastructure challenges. By implementing strategic policies, Kazakhstan can accelerate robotics adoption, enhance industrial productivity, and integrate into the global high-tech economy.

1. Qiu S. et al. Deep learning techniques in intelligent fault diagnosis and prognosis for industrial systems: a review // Sensors. 2023. Vol. 23. No. 3. P. 1305.

2. Al Noman M.A., Zhai L., Almukhtar F H., Rahaman M.F., Omarov B., Ray S., Wang C. A computer vision-based lane detection technique using gradient threshold and hue-lightness-saturation value for an autonomous vehicle // International Journal of Electrical and Computer Engineering. 2023. Vol. 13. No. 1. P. 347.

3. Temirgaziyeva S., Omarov B. Traffic sign recognition with convolutional neural network // Scientific Journal of Astana IT University. 2022. P. 14–23.

4. Faccio M. et al. Human factors in cobot era: a review of modern production systems features // Journal of Intelligent Manufacturing. 2023. Vol. 34. No. 1. P. 85–106.

5. Dzedzickis A. et al. Advanced applications of industrial robotics: New trends and possibilities // Applied Sciences. 2021. Vol. 12. No. 1. P. 135.

6. Galin R., Meshcheryakov R. Automation and robotics in the context of Industry 4.0: the shift to collaborative robots // IOP Conference Series: Materials Science and Engineering. IOP Publishing, 2019. Vol. 537. No. 3. P. 032073.

7. Baimukhanov T. et al. Some aspects of robotization of the economy and creation of a robot manager // Journal of Economic Research & Business Administration. 2021. Vol. 137. No. 3. P. 139–146.

8. Daribay A., Serikova A., Ukaegbu I.A. Industry 4.0: Kazakhstani industrialization needs a global perspective // Procedia computer science. 2019. Vol. 151. P. 903–908.

9. Sotnik S., Lyashenko V. Modern industrial robotics industry. 2022.

10. Ступина Е.Е. и др. Основы робототехники: учебное пособие для студентов вузов. – 2019.

11. Mamrayeva D.G., Toxambayeva A.B., Tashenova L.V. Industry digitalization in the Republic of Kazakhstan // Bulletin of the Karaganda university Economy series. 2022. Vol. 105. No. 1. P. 54–67.

12. George A.S., George A.S.H. Revolutionizing Manufacturing: Exploring the Promises and Challenges of Industry 5.0 // Partners Universal International Innovation Journal. 2023. Vol. 1. No. 2. P. 22–38.

13. Javaid M., Haleem A., Singh R.P., Suman R., Javaid M. et al. Artificial intelligence applications for industry 4.0: A literature-based study // Journal of Industrial Integration and Management. 2022. Vol. 7. No. 01. P. 83–111.

14. Qazaqstan Respublikasy strategialyq josparlau jäne reformalar jönındegı agenttıgınıñ ūlttyq statistika bürosy. URL: https://www.stat.gov.kz/ (ötınış berılgen kün: 21.11.2024). (In Kazakh).

15. Bhadra P., Chakrabort, S., Saha S. Cognitive IoT Meets Robotic Process Automation: The Unique Convergence Revolutionizing Digital Transformation in the Industry 4.0 Era. In Confluence of Artificial Intelligence and Robotic Process Automation. Singapore: Springer Nature Singapore, 2023, pp. 355–388.