ARTIFICIAL INTELLIGENCE ADOPTION IN THE “TRANSPORTATION AND STORAGE” SECTOR IN THE EUROPEAN UNION: AN EMPIRICAL ANALYSIS OF TRENDS AND BARRIERS

Krasimir Petkov

Scientific paper ID 2773 : 2026/1

ARTIFICIAL INTELLIGENCE ADOPTION IN THE “TRANSPORTATION AND STORAGE” SECTOR IN THE EUROPEAN UNION: AN EMPIRICAL ANALYSIS OF TRENDS AND BARRIERS

Krasimir Petkov

Digital transformation is a strategic priority of the European Union, with artificial intelligence (AI) playing a key role in enhancing competitiveness and sustainability within the “Transportation and Storage” sector (NACE Rev. 2, Section H). The study examines the levels of AI adoption and the barriers faced by enterprises in this sector across the EU-27, using Eurostat data. The findings indicate a gradual change until 2023, followed by acceleration in 2024–2025, driven primarily by generative AI applications such as AI for image/video/audio generation, natural language processing (NLP), and speech recognition. The main barriers identified lack of expertise, legal uncertainty, and concerns regarding data protection. The post-2023 acceleration reflects increased availability of AI solutions and EU policy initiatives (including Regulation (EU) 2024/1689), however, structural characteristics of the sector constrain large-scale AI deployment. There is a clear need for targeted measures supporting digital skills development, standardization, and data governance.

• Reload article • Open/Download as PDF

изкуствен интелект транспорт и складиране внедряване на ИИ бариери пред ИИ дигитална трансформация Европейски съюзartificial intelligence transportation and storage AI adoption AI barriers digital transformation European UnionKrasimir Petkov

BIBLIOGRAPHY

[1] Abduljabbar, R., Dia, H., Liyanage, S., & Bagloee, S. A. (2019). Applications of artificial intelligence in transport: An overview. Sustainability, 11(1), 189. https://doi.org/10.3390/su11010189

[2] Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108 ...

[3] Biolcheva, P., & Molhova-Vladova, M. (2025). Business Assessment of the Indirect Added Value of AI. Advances in Management and Applied Economics, 65–75. https://doi.org/10.47260/amae/1534

[4] Biolcheva, P., & Sterev, N. (2024). A Model for Calculating the Indirect Added Value of AI for Business. Strategies for Policy in Science and Education-Strategii Na Obrazovatelnata i Nauchnata Politika, 32(3s), 9–17. https://doi.org/10.53656/str2024-3s-1-mod

[5] Boșcoianu, M., Tóth, Z., & Goga, A. (2025). Sustainable Strategies to Reduce Logistics Costs Based on Cross-Docking—The Case of Emerging European Markets. Sustainability. https://doi.org/10.3390/su17146471

[6] Chen, W., Men, Y., Fuster, N., Osorio, C., & Juan, A. (2024). Artificial Intelligence in Logistics Optimization with Sustainable Criteria: A Review. Sustainability. https://doi.org/10.3390/su16219145

[7] Chung, S. (2021). Applications of smart technologies in logistics and transport: A review. Transportation Research Part E-logistics and Transportation Review, 153, 102455. https://doi.org/10.1016/j.tre.2021.102455

[8] European Commission. (2019). The European Green Deal. COM(2019) 640 final. Brussels: European Commission.

[9] European Commission. (2020a). White Paper on Artificial Intelligence – A European approach to excellence and trust. COM(2020) 65 final. Brussels: European Commission.

[10] European Commission. (2020b). A European strategy for data. COM(2020) 66 final. Brussels: European Commission.

[11] European Commission. (2021a). Fostering a European approach to Artificial Intelligence. COM(2021) 205 final. Brussels: European Commission.

[12] European Commission. (2021b). Europe’s Digital Decade: Digital targets for 2030. COM(2021) 118 final. Brussels: European Commission.

[13] European Commission. (2021c). Proposal for a Regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). COM(2021) 206 final. Brussels: European Commission.

[14] European Communities. (2008). NACE Rev. 2 Statistical classification of economic activities in the European Community (Methodologies and Working Papers).

[15] Eurostat. (2025). Use of artificial intelligence in enterprises. Statistics Explained, European Commission. https://ec.europa.eu/eurostat/statistics-ex...

[16] Guerrero-Ibáñez, J., Zeadally, S., & Contreras-Castillo, J. (2018). Sensor technologies for intelligent transportation systems. Sensors, 18(4), 1212. https://doi.org/10.3390/s18041212

[17] Ieva, S., Bilenchi, I., Gramegna, F., Pinto, A., Scioscia, F., Ruta, M., & Loseto, G. (2025). Enhancing Last-Mile Logistics: AI-Driven Fleet Optimization, Mixed Reality, and Large Language Model Assistants for Warehouse Operations. Sensors (Basel, Switzerland), 25. https://doi.org/10.3390/s25092696

[18] Jackson, I., Ivanov, D., Dolgui, A., & Namdar, J. (2024). Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation. International Journal of Production Research, 62, 6120 - 6145. https://doi.org/10.1080/00207543.2024.23093...

[19] Kshetri, N. (2021). Artificial intelligence in developing countries’ transportation systems. IT Professional, 23(2), 63–68. https://doi.org/10.1109/MITP.2021.3058652

[20] Kückelhaus, M., & Chung, A. (2019). Artificial intelligence in logistics. DHL Customer Solutions & Innovation. Troisdorf: DHL.

[21] Laux, J., Wachter, S., & Mittelstadt, B. (2023). Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk. Regulation & Governance, 18, 3 - 32. https://doi.org/10.1111/rego.12512

[22] Mahroof, K. (2019). A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse. Int. J. Inf. Manag., 45, 176-190. https://doi.org/10.1016/j.ijinfomgt.2018.11...

[23] Mazurencu-Marinescu-Pele, M., Poleac, D., Chicu, N., Pele, D., & Bogdan, A. (2025). AI Adoption in EU Enterprises: a Comprehensive Analysis and Modelling of Usage Patterns, Sectoral Differences and Acquisition Trends. Statistika: Statistics and Economy Journal. https://doi.org/10.54694/stat.2024.75

[24] Milakis, D., Van Arem, B., & Van Wee, B. (2017). Policy and society related implications of automated driving: A review of literature and directions for future research. Journal of Intelligent Transportation Systems, 21(4), 324–348. https://doi.org/10.1080/15472450.2017.12913...

[25] OECD. (2020). Digital transformation in the age of COVID-19: Building resilience and bridging divides. Digital Economy Papers No. 323. Paris: OECD Publishing.

[26] Oldemeyer, L., Jede, A., & Teuteberg, F. (2024). Investigation of artificial intelligence in SMEs: a systematic review of the state of the art and the main implementation challenges. Management Review Quarterly, 75, 1185 - 1227. https://doi.org/10.1007/s11301-024-00405-4 ...

[27] Richey, R., Chowdhury, S., Davis‐Sramek, B., Giannakis, M., & Dwivedi, Y. (2023). Artificial intelligence in logistics and supply chain management: A primer and roadmap for research. Journal of Business Logistics. https://doi.org/10.1111/jbl.12364

[28] Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

[29] Taeihagh, A., & Lim, H. S. M. (2019). Governing autonomous vehicles: Emerging responses for safety, liability, privacy, cybersecurity, and industry risks. Transport Reviews, 39(1), 103–128. https://doi.org/10.1080/01441647.2018.14946...

[30] Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2020.09.0...

[31] Zrelli, I., & Rejeb, A. (2024). A bibliometric analysis of IoT applications in logistics and supply chain management. Heliyon, 10. https://doi.org/10.1016/j.heliyon.2024.e365...

[32] Gatovski, I., & Arnaudov, B. (2023). Tendentsii v razvitieto na transportnata infrastruktura v Balgariya. Ikonomicheski i sotsialni alternativi, (2), 5-23. DOI: https://doi.org/10.37075/ISA.2023.2.01
( [32] Гътовски, И., & Арнаудов, Б. (2023). Тенденции в развитието на транспортната инфраструктура в България. Икономически и социални алтернативи, (2), 5-23. DOI: https://doi.org/10.37075/ISA.2023.2.01 )

[33] Dimitrov, D., & Gergova, N. (2024). Visoko tehnologichni vazmozhnosti i instrumenti za izpolzvane na izkustveniya intelekt (AI) v sferata na transportnoto obrazovanie. Mehanika, Transport, Komunikatsii, 22(3/1).
( [33] Димитров, Д., & Гергова, Н. (2024). Високо технологични възможности и инструменти за използване на изкуствения интелект (AI) в сферата на транспортното образование. Механика, Транспорт, Комуникации, 22(3/1). )

[34] Yordanov, D. (2023). Otrazhenie na COVID-19 varhu deynostta na sektor transport. Nauchni trudove na UNSS, (3), 79–105. https://doi.org/10.37075/RP.2023.3.05
( [34] Йорданов, Д. (2023). Отражение на COVID-19 върху дейността на сектор транспорт. Научни трудове на УНСС, (3), 79–105. https://doi.org/10.37075/RP.2023.3.05 )