Communications - Scientific letters of the University of Zilina X:X | DOI: 10.26552/com.C.2026.030

Digital Transformation and Artificial Intelligence: New Opportunities for Economic Growth in the Logistics Industry

Nelli Akylbekova ORCID...1,*, Bin Zhang ORCID...2, Congcong Liu ORCID...3, Yujie Liu ORCID...2, Yi Zhuo ORCID...3
1 Kyrgyz National University named after Jusup Balasagyn, Institute of Management and Business, Bishkek, Kyrgyz Republic
2 Kyrgyz State University named after I. Arabaev, Bishkek, Kyrgyz Republic
3 Kyrgyz National University named after Jusup Balasagyn, Bishkek, Kyrgyz Republic

To remain competitive, authorities had to apply artificial intelligence, especially in logistics. This study’s aim was to examine how the digital transformation and artificial intelligence create new opportunities for economic growth in the logistics industry, with a particular focus on Kyrgyzstan. Implementation remains low. Policies aim to develop the sector but are insufficient for international competitiveness. The AI can address logistical challenges, optimize routes, improve management, and reduce costs. The key issues - low digitalization, shortage of specialists, and weak infrastructure - can be mitigated through sound policies. The results provide insights for policymakers and industry stakeholders on leveraging AI and digital transformation to boost economic performance in logistics.

Keywords: Big Data, transport sector, innovations, tools, public policy
Grants and funding:

The authors received no financial support for the research, authorship and/or publication of this article.

Conflicts of interest:

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Received: January 20, 2026; Accepted: May 6, 2026; Prepublished online: May 6, 2026 

Download citation

References

  1. VIKHROV, I., ASHIRBAEV, S., KADIROVA, M. Publication activity of Central Asian scientists on artificial intelligence including medicine. Journal of Interdisciplinary Approaches to Medicine [online]. 2022, 3(1), p. 72-77. ISSN 2709-2968, eISSN 2709-2976. Available from: https://doi.org/10.26577/IAM.2022.v3.i1.012 Go to original source...
  2. ONDASH, A.A. Artificial intelligence and problems of its legal regulation. Bulletin of the National Academy of Sciences of the Kyrgyz Republic. 2023, 3, p. 243-248. ISSN 2307-521X.
  3. ISAEV, E., ERMANOVA, M., SIDLE, R. C., ZAGINAEV, V., KULIKOV, M., CHONTOEV, D. Reconstruction of hydrometeorological data using dendrochronology and machine learning approaches to bias-correct climate models in Northern Tien Shan, Kyrgyzstan. Water [online]. 2022, 14(15), 2297. eISSN 2073-4441. Available from: https://doi.org/10.3390/w14152297 Go to original source...
  4. SALMORBEKOVA, R., KURMANOV, U. E. Methodology of transport and logistics systems of the Kyrgyz Republic. ISRG Journal of Multidisciplinary Studies [online]. 2024, 2(8), p. 14-19. eISSN 2584-0452. Available from: https://doi.org/10.5281/zenodo.13352655 Go to original source...
  5. KOMENDANTOVA, N., ROVENSKAYA, E., STRELKOVSKII, E., RODRIGUEZ, F. S. Impacts of various connectivity processes in Central Asia on sustainable development of Kyrgyzstan. Sustainability [online]. 2022, 14(12), 6998. eISSN 2071-1050. Available from: https://doi.org/10.3390/su14126998 Go to original source...
  6. QIN, Y., XU, Z., WANG, X., SKARE, M. Artificial intelligence and economic development: an evolutionary investigation and systematic review. Journal of the Knowledge Economy [online]. 2023, 15(1), p. 1736-1770. eISSN 1868-7873. Available from: https://doi.org/10.1007/s13132-023-01183-2 Go to original source...
  7. BAG, S., PRETORIUS, H. J. C., GUPTA, S., DWIVEDI, Y. K. Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities. Technological Forecasting and Social Change [online]. 2021, 163(5), 120420. ISSN 0040-1625, eISSN 1873-5509. Available from: https://doi.org/10.1016/j.techfore.2020.120420 Go to original source...
  8. HEROLD, D. M., CWIKLICKI, M., PILCH, K., MIKL, J. The emergence and adoption of digitalization in the logistics and supply chain industry: an institutional perspective. Journal of Enterprise Information Management [online]. 2021, 34(6), p. 1917-1938. ISSN 1758-7409, eISSN 1741-0398. Available from: https://doi.org/10.1108/JEIM-09-2020-0382 Go to original source...
  9. GUPTA, A., SINGH, R. K., GUPTA, S. Developing human resources for the digitization of logistics operations: readiness index framework. International Journal of Manpower [online]. 2021, 43(2), p. 355-379. ISSN 0143-7720, eISSN 1758-6577, Available from: https://doi.org/10.1108/IJM-03-2021-0175 Go to original source...
  10. CICHOSZ, M., WALLENBURG, C. M., KNEMEYER, A. M. Digital transformation at logistics service providers: barriers, success factors and leading practices. International Journal of Logistics Management [online]. 2020, 31(2), p. 209-238. ISSN 0957-4093, eISSN 1758-6550. Available from: https://doi.org/10.1108/IJLM-08-2019-0229 Go to original source...
  11. RICHEY, R. G., CHOWDHURY, S., DAVIS-SRAMEK, B., GIANNARIS, M., DWIVEDI, Y. K. Artificial intelligence in logistics and supply chain management: a primer and roadmap for research. Journal of Business Logistics [online]. 2023, 44(4), p. 532-549. ISSN 0735-3766, eISSN 2158-1592. Available from: https://doi.org/10.1111/jbl.12364 Go to original source...
  12. CHUNG, S.-H. Applications of smart technologies in logistics and transport: a review. Transportation Research Part E: Logistics and Transportation Review [online]. 2021, 153(2), 102455. ISSN 1366-5545, eISSN 1878-5794. Available from: https://doi.org/10.1016/j.tre.2021.102455 Go to original source...
  13. NWAGWU, U., NIAZ, M., CHUKWU, M. U., SADDIQUE, F. The influence of artificial intelligence to enhancing supply chain performance under the mediating significance of supply chain collaboration in manufacturing and logistics organizations in Pakistan. Traditional Journal of Multidisciplinary Sciences. 2023, 1(2), p. 29-40.
  14. EYO-UDO, N. L. Leveraging artificial intelligence for enhanced supply chain optimization. Open Access Research Journal of Multidisciplinary Studies [online]. 2024, 7(2), p. 1-15. eISSN 2783-0268. Available from: https://doi.org/10.53022/oarjms.2024.7.2.0044 Go to original source...
  15. SIREESHA, P., SULTANA, S. Artificial intelligence in logistics. International Journal of Research [online]. 2024, 11(1), p. 1-9. ISSN 2348-795X, eISSN 2348-6848. Available from: https://ijrjournal.com/index.php/ijr/article/view/1198
  16. CULOT, G., PODRECCA, M., NASSIMBENI, G. Artificial intelligence in supply chain management: a systematic literature review of empirical studies and research directions. Computers in Industry [online]. 2024, 162, 104132. ISSN 0166-3615, eISSN 1872-6194. Available from: https://doi.org/10.1016/j.compind.2024.104132 Go to original source...
  17. TAN, L., CHAN, M. Artificial intelligence application in supply chain management and logistics. Innovation and Technology Studies [online]. 2024, 1(1), p. 10-16. ISSN 3007-6919, eISSN 3007-6927. Available from: https://doi.org/10.61784/its3004 Go to original source...
  18. LIU, T. Optimizing supply chain logistics using AI-driven predictive analytics. International Transactions on Artificial Intelligence (ITAI) [online]. 2024, 4(4). Available from: https://journals.enfoundations.com/index.php/ITAI/article/view/41 Go to original source...
  19. DMITRIYEVA, A. Artificial intelligence and knowledge research networks between Central Asia and the European Union: A bibliometric study 2000-2025. Iberoamerican Journal of Science Measurement and Communication [online]. 2025, 5(4), p. 1-10. ISSN 2709-7595, eISSN 2709-3158. Available from: https://doi.org/10.47909/ijsmc.277 Go to original source...
  20. Cumulative AI-related bills passed into law since 2016, as of 2023. 2023a - Our World in Data [online]. Available from: https://ourworldindata.org/grapher/cumulative-number-artificial-intelligence-bills-passed?tab=table&country=~KGZ
  21. Annual scholarly publications on artificial intelligence. 2023b - Our World in Data [online]. Available from: https://ourworldindata.org/grapher/annual-scholarly-publications-on-artificial-intelligence?tab=table&time=2013..latest&country=~KGZ
  22. Scholarly publications on artificial intelligence per million people. 2023c - Our World in Data [online]. Available from: https://ourworldindata.org/grapher/scholarly-publications-on-artificial-intelligence-per-million-people?tab=chart&country=KGZ
  23. Annex to the Decree of the President of the Kyrgyz Republic No. 90 Concept "Digital transformation of the Kyrgyz Republic for 2024-2028" [online]. 2024. Available from: https://digital.gov.kg/wp-content/uploads/2024/06/concept-digital-transformation-of-the-kyrgyz-republic-for-2024-2028.pdf
  24. Kyrgyzstan actively works on implementation and use of AI. 2024 - KABAR [online]. Available from: https://en.kabar.kg/news/kyrgyzstan-actively-works-on-implementation-and-use-of-ai/
  25. IBM Watson [online]. 2024. Available from: https://www.ibm.com/watson
  26. Amazon Robotics [online]. 2024. Available from: https://www.aboutamazon.com/news/tag/robotics
  27. How route optimization keeps UPS drivers on time. 2024 - ORION [online]. Available from: https://www.roundtrip.ai/articles/ups-route-optimization-software
  28. SAP Ariba [online]. 2024. Available from: https://www.sap.com/products/spend-management/ariba-login.html
  29. DOLZHENKO, N., ASSILBEKOVA, I., KONAKBAY, Z., GARMASH, O., MURATBEKOVA, G. Organization of Transport Services and Transport Process Safety. Periodica Polytechnica Transportation Engineering [online]. 2025, 53(3), p. 277-291. ISSN 1587-3811. Available from: https://doi.org/10.3311/PPtr.38137 Go to original source...
  30. LUKASH, M., CHUPRUN, Y., LYSAK, O., HUSAKOVSKYI, A., HANHANOV, K. AI evolution and its role in transforming the automation of commercial activities. LatIA [online]. 2025, 3, 344. ISSN 3046-403X. Available from: https://doi.org/10.62486/latia2025344 Go to original source...
  31. MERONO-PENUELA, A., SIMPERL, E., KURTEVA, A., REKLOS, I. KG.GOV: Knowledge graphs as the backbone of data governance in AI. Journal of Web Semantics [online]. 2025, 85, 100847. eISSN 1873-7749. Available from: https://doi.org/10.1016/j.websem.2024.100847 Go to original source...
  32. KAIRATKYZY, G., KARSYBAYEV, Y. Y., ABZHAPBAROVA, A. Z., DERYUGIN, O. V., BAS, I. K. Improving the reliability of trucking in the conditions of a mining enterprise. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu / Scientific Bulletin of the National Mining University [online]. 2022, 3, p. 125-130. ISSN 2223-2362. Available from: https://doi.org/10.33271/nvngu/2022-3/125 Go to original source...
  33. CHERNIAVSKA, T., CHERNIAVSKYI, B., SANIKIDZE, T., SHARASHENIDZE, A., TORTLADZE, M., BULEISHVILI, M. Optimization of medical logistics with bee colony algorithms in emergency, military conflict and post-war remediation settings. CEUR Workshop Proceedings [online]. 2024, 3892, p. 220-235. ISSN 1613-0073. Available from: https://ceur-ws.org/Vol-3892/paper16.pdf
  34. BOCCACCIO, A., CASCELLA, G. L., FIORENTINO, M., MANGHISI, V. M., MONNO, G., UVA, A. E. Exploiting augmented reality to display technical information on industry 4.0 P&ID. In: Lecture Notes in Mechanical Engineering [online]. Conference paper. 2019. 978-3-030-12346-8, pp. 282-291. Available from: https://doi.org/10.1007/978-3-030-12346-8_28 Go to original source...
  35. COSTANTINO, D., BRESCIA, E., MASSENIO, P. R., SERAFINO, P., CASCELLA, G.L., CUPERTINO, F. SuMRAS: A new SPMSM parameter identification in cloud computing environment. In: Proceedings - 2021 IEEE Workshop on Electrical Machines Design, Control and Diagnosis [online]. WEMDCD. 2021. ISBN 978-1-7281-7615-4, p. 297-302. Available from: https://doi.org/10.1109/WEMDCD51469.2021.9425641 Go to original source...
  36. CHERNIAVSKA, T., CHERNIAVSKYI, B. Architecture-oriented agent-based model (AOAM) for optimizing transport evacuation management and emergency medical assistance in the context of the war in Ukraine: challenges and prospects. CEUR Workshop Proceedings [online]. 2024, 3892, p. 319-336. ISSN 1613-0073 Available from: https://ceur-ws.org/Vol-3892/paper21.pdf
  37. BARLYBAYEV, A., SHARIPBAY, A., SHAKHMETOVA, G., ZHUMADILLAYEVA, A. Development of a Flexible Information Security Risk Model Using Machine Learning Methods and Ontologies. Applied Sciences (Switzerland) [online]. 2024, 14(21), 9858. ISSN 2076-3417. Available from: https://doi.org/10.3390/app14219858 Go to original source...
  38. KUBICZEK, J., ROSZKO-WOJTOWICZ, E., KOCZY, J., WASZKIEWICZ, I., WOS, K. Harnessing AI for business transformation: strategies for effective implementation and market advantage. Statistics in Transition New Series [online]. 2025, 26(2), p. 199-213. ISSN 2450-0291. Available from: https://doi.org/10.59139/stattrans-2025-022 Go to original source...
  39. MATKARIMOV, B., BARLYBAYEV, A., KARIMOV, D. Enhancing Analytical Precision in Company Earnings Reports through Neurofuzzy System Development: A Comprehensive Investigation. Journal of Electrical and Computer Engineering [online]. 2024, 2024, 8515203. ISSN 2090-0147. Available from: https://doi.org/10.1155/2024/8515203 Go to original source...
  40. BIJU, A. K. V. N., THOMAS, A. S., THASNEEM, J. Examining the research taxonomy of artificial intelligence, deep learning and machine learning in the financial sphere - a bibliometric analysis. Quality and Quantity [online]. 2023, 58(1), p. 849-878. ISSN 0033-5177, eISSN 1573-7845. Available from: https://doi.org/10.1007/s11135-023-01673-0 Go to original source...
  41. CHALLOUMIS, C. Charting the course - the impact on AI on global economic cycles. In: XVI International Scientific Conference Current Questions of Modern Science: proceedings [online]. World of Conferences. 2024. ISBN 978-92-44514-24-5, p. 103-127. Available from: https://doi.org/10.5281/zenodo.14003554 Go to original source...
  42. BOINAPALLI, N. R. Digital transformation in U.S. industries: AI as a catalyst for sustainable growth. NEXG AI Review of America [online]. 2020, 1(1), p. 70-84. Available from: https://nexgaireview.com/article/view/6

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.