Journals / ASSAM Uluslararası Hakemli Dergi / 2026 / Sayı: 28

Using Artifıcial Intelligence For Enhancing E-Commerce In Foreign Trade

ULUSLARARASI TİCARETTE E-TICARETİ GELİŞTİRMEK İÇİN YAPAY ZEKA KULLANIMI

Tuğçenur Ekinci Furtana(İSTANBUL SABAHATTİN ZAİM ÜNİVERSİTESİ)0000-0002-8495-9432
Ameen Abdelbaset Ali Omar Abdelmalik(ISTANBUL SABAHATTIN ZAIM UNIVERSITY, INSTITUTE OF SOCIAL SCIENCES)0009-0002-5097-1190
Pages
17–32
Publication Date
2026-01-21
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings reveal that AI integration leads to substantial improvements in operational efficiency, accuracy in forecasting, and heightened customer engagement.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In the context of global trade, e-commerce faces numerous challenges, including complex customs procedures, diverse payment systems, cultural and language barriers, and intricate logistics.
📊
Key Findings & Data:These areas include supply chain optimization, inventory management, personalized marketing strategies, and facilitation of cross-border transactions.
💡
Conclusion & Impact:The findings reveal that AI integration leads to substantial improvements in operational efficiency, accuracy in forecasting, and heightened customer engagement.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yapay Zeka · E-Ticaret · Dış Ticaret

Abstract

In the context of global trade, e-commerce faces numerous challenges, including complex customs procedures, diverse payment systems, cultural and language barriers, and intricate logistics. This thesis investigates how artificial intelligence (AI) can be harnessed to overcome these obstacles and enhance e-commerce operations in foreign trade. Utilizing a single-method research approach that includes interviews, this study investigates the implementation of artificial intelligence technologies, including machine learning, natural language processing, and computer vision, within critical sectors of e-commerce. These areas include supply chain optimization, inventory management, personalized marketing strategies, and facilitation of cross-border transactions. The findings reveal that AI integration leads to substantial improvements in operational efficiency, accuracy in forecasting, and heightened customer engagement. The study also emphasizes how AI can strengthen international trade procedures, save expenses, and promote global market access for companies of all kinds. The thesis concludes with actionable recommendations for e-commerce enterprises, policymakers, and technology developers to increase the advantages of AI while adopting ethical and regulatory considerations. Additionally, it highlights potential avenues for future research to deepen the understanding of AI's evolving impact on international e-commerce.

Özet

Küresel ticaret bağlamında e-ticaret, karmaşık gümrük prosedürleri, çeşitli ödeme sistemleri, kültürel ve dil engelleri ile karmaşık lojistik gibi birçok zorlukla karşı karşıyadır. Bu tez, yapay zekânın (AI) bu engelleri aşmak ve dış ticarette e-ticaret operasyonlarını geliştirmek için nasıl kullanılabileceğini araştırmaktadır. Görüşmeleri içeren tek yöntemli bir araştırma yaklaşımının kullanılmasıyla, çalışma, makine öğrenimi, doğal dil işleme ve bilgisayar görüşü gibi yapay zekâ teknolojilerinin e-ticaretin temel alanlarında uygulanmasını incelemektedir. Bu alanlar arasında tedarik zinciri optimizasyonu, envanter yönetimi, kişiselleştirilmiş pazarlama stratejileri ve sınır ötesi işlemlerin kolaylaştırılması yer almaktadır. Bulgular, yapay zekâ entegrasyonunun operasyonel verimlilikte önemli iyileşmelere, tahmin doğruluğunda artışa ve müşteri katılımında yükselişe yol açtığını ortaya koymaktadır. Ayrıca, araştırma, yapay zekânın uluslararası ticaret süreçlerini kolaylaştırma, maliyetleri düşürme ve her büyüklükteki işletme için küresel pazar erişimini teşvik etme potansiyelini vurgulamaktadır. Tez, e-ticaret işletmeleri, politika yapıcılar ve teknoloji geliştiriciler için yapay zekânın faydalarını maksimize ederken etik ve düzenleyici hususları ele almak üzere uygulanabilir önerilerle sona ermektedir. Ayrıca, uluslararası e-ticarette yapay zekânın gelişen rolünü daha fazla keşfetmek için gelecekteki araştırma alanlarını belirlemektedir.

🔖

Cite This Article

Furtana, T. E., Abdelmalik, A. A. A. O. (2026). Using Artifıcial Intelligence For Enhancing E-Commerce In Foreign Trade. ASSAM Uluslararası Hakemli Dergi, Sayı: 28, 17–32. https://doi.org/10.58724/assam.1748821

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (69)

  1. 247Commerce. (2024). AI-Powered E-Commerce: Benefits and Challenges - 247 Commerce. AI-Powered E-Commerce.
  2. Alicke, K., Dilda, V., Görner, S., Mori, L., Rebuffel, P., Reiter, S., & Samek, R. (2021). Succeeding in the AI supply-chain revolution. New York: McKinsey & Company.
  3. Amazon. (2024, October 09). Amazon unveils the next generation of fulfillment centers powered by AI and 10 times more robotics. Retrieved from Amazon: https://www.aboutamazon.com/news/operations/amazon-fulfillment-center-robotics-ai
  4. Ashfaq, S. (2023). Artificial Intelligence in E-commerce: Benefits, and Challenges. Artificial Intelligence in E-commerce.
  5. Babatunde, S. O., Odejide, O. A., Edunjobi, T. E., & Ogundipe, D. O. (2024). The Role Of Ai In Marketing Personalization: A Theoretical Exploration Of Consumer Engagement Strategies. International Journal of Management & Entrepreneurship Research, 936-949.
  6. Bawack, R. E., Wamba, S. F., Carillo, K. D., & Akter, S. (2022). Artificial intelligence in E-Commerce: a bibliometric study and literature review. Electronic Markets, 297–338.
  7. Bertovich, Y. (2025, May 1). Ethical AI in Ecommerce: Best Practices for Building Trust and Ensuring Transparency. Retrieved from Salsify: https://www.salsify.com/blog/what-is-ethical-ai-in-ecommerce
  8. Brachman, R., & Levesque, H. (2004). Knowledge Representation and Reasoning. Elsevier.
  9. Brown, J. (2024, November 26). AI-Driven E-commerce Development: What to Expect in 2025 and Beyond. Retrieved from Kozak Group: https://kozak-group.com/ai-driven-e-commerce-development-what-to-expect-in-2025-and-beyond/
  10. Chen, D., & Wang, J. P. (2022 ). The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms. Frontiers in Psychology, 1-14.
  11. Chaturvedi, N., Martich, M., Ruwadi, B., & Ulker, N. (2021). The Future of Retail Supply Chains. Retail Insights, 59-67.
  12. Codiant. (2024, March 18). AI to Scale E-Commerce Platforms: Challenges and Solutions. Retrieved from Codiant: https://codiant.com/blog/ai-to-scale-e-commerce-platforms-challenges-and-solutions/ DHL. (2024). Logistics Trend Radar. Leipzig: DHL International.
  13. Downie, A., & Finn, T. (2024, May 20). What is AI in supply chain? Retrieved from IBM: https://www.ibm.com/think/topics/ai-supply-chain
  14. Dr. N. VENKATESAN, B. P. (2025). Ethical Implications of Ai In E-Commerce: Balancing Innovation With Data Privacy And Fairness. South Eastern European Journal of Public Health, 1655-1666.
  15. Easdon-Smith, C. (2024 ). Firework | How AI Is Changing Ecommerce Personalization. Retrieved from Firework: https://www.firework.com/blog/how-ai-is-changing-ecommerce-personalization
  16. ESCAP. (2025, February 18). Shaping AI Rules Through Trade Agreements. Retrieved from ESCAP: https://www.unescap.org/blog/shaping-ai-rules-through-trade-agreements
  17. European Commission. (2025, February 18 ). AI Act. Retrieved from Shaping Europe’s digital future: https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
  18. Girimurugan, B., V.Kumaresan, Nair, S. G., Kuchi, M., T., M. S., & Kholifah, N. (2024). AI and Machine Learning in E-Commerce Security: Emerging Trends and Practices. In Strategies for E-Commerce Data Security: Cloud, Blockchain, AI, and Machine Learning (pp. 29-53). IGI Global Scientific Publishing.
  19. Gomez, G. (2024, July 4). The Benefits and Challenges of AI in E-commerce. Retrieved from AJAW: https://ajawmrp.com/the-benefits-and-challenges-of-ai-in-e-commerce/
  20. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. London: MIT Press.
  21. Hengesbaugh, B., & Denham, E. (2024, November 5 ). A glimpse into the future of cross-border data regulation. Retrieved from IAPP: https://iapp.org/news/a/a-glimpse-into-the-future-of-cross-border-data-regulation
  22. Jakkula, A. R. (2022). Challenges in Implementing AI in E-Commerce and How to Overcome Them. Journal of Artificial Intelligence & Cloud Computing, 1-3.
  23. Javier López González, M.-A. J. (2017). Digital trade: Developing A Framework For Analysis. Paris: OECD Publications.
  24. Jurafsky, D., & Martin, J. H. (2025). Speech and Language Processing. California: Stanford University.
  25. Keohane, D. (2025, May 16 ). Japan weighs privacy rules against treatments in healthcare. Retrieved from Financial Times: https://www.ft.com/content/f4e81b4c-d0b6-40ef-89c5-3f69a6a26574
  26. Konrad Meier, R. S. (2024, March 15 ). The EU AI Act: What it means for your business. Retrieved from Ernst & Young Limited: https://www.ey.com/en_ch/insights/forensic-integrity-services/the-eu-ai-act-what-it-means-for-your-business
  27. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 436–444.
  28. McCarthy, J. (2007). WHAT IS ARTIFICIAL INTELLIGENCE? California: Stanford University.
  29. Medida, L. (2024, July 30). The Rise of Conversational Commerce: Revolutionizing Customer Support and Boosting Conversion Rates. Retrieved from kensium: https://www.kensium.com/blog/the-rise-of-conversational-commerce-revolutionizing-customer-support-and-boosting-conversion-rates
  30. Mishova, A. (2025, January 23). AI Regulations and the Future of Global Data Protection. Retrieved from GDPR Local: https://gdprlocal.com/ai-regulations-and-the-future-of-global-data-protection/
  31. Ocampo, D. (2024, June ). CCPA and the EU AI ACT. Retrieved from California Lawyer’s Association’s: https://calawyers.org/privacy-law/ccpa-and-the-eu-ai-act/
  32. OECD. (2019). Unpacking E commerce: BUSINESS MODELS, TRENDS AND POLICIES. Paris: OECD publications.
  33. Ozturk, O. (2024). The Impact of AI on International Trade: Opportunities and Challenges. Economies, 1-13.
  34. Ren, Q., Jiang, Z., Cao, J., Li, S., Li, C., Liu, Y.,. Chen, Y. (2024). A survey on fairness of large language models in e-commerce: progress, application, and challenge. New York: Cornell University.
  35. Russell, S. J., & Norvig, P. (2022). Artificial Intelligence: A Modern Approach. Harlow: Pearson Education Limited.
  36. Schulz, M. (2025, May 6). Could ChatGPT fix online shopping? Retrieved from Vogue Business: https://www.voguebusiness.com/story/technology/could-chatgpt-fix-online-shopping
  37. Sherman, N. (2024, January 25). AI Regulations around the World - 2025. Retrieved from Mind Foundry: https://www.mindfoundry.ai/blog/ai-regulations-around-the-world
  38. Singla, A. (2024, May 30). The state of AI in early 2024: Gen AI adoption spikes and starts to generate value. Retrieved from QuantumBlack AI by Mckinsey: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2024
  39. Szeliski, R. (2021). Computer Vision: Algorithms and Applications. Springer.
  40. The Australian. (2024, April 1). AI filtering out women in job searches: Nuix. Retrieved from The Australian: https://www.theaustralian.com.au/business/technology/ai-filtering-out-women-who-have-taken-maternity-leave-in-job-searches-nuix/news-story/446ea0e1f5bd02868fca242b38d7efba
  41. The OECD Observer. (1999). Six Aspects of Electronic Commerce. Paris: OECD Publications.
  42. Thornhill, J. (2025, May 15). US AI laws risk becoming more ‘European’ than Europe’s. Retrieved from Financial Times: https://www.ft.com/content/aed82f47-b441-4bb3-930e-eca10585fc6d
  43. Tiwari, S., Wee, H., & Daryanto, Y. (2018). Big data analytics in supply chain management between 2010 and 2016: Insights to industries. Computers & Industrial Engineering, 319-330.
  44. Tomitza, C., Ibrahimli, U., & Herm, L.-V. (2024). AI-Based Methods of Dynamic Pricing in E-Commerce: A Systematization of Literature. AI-based Pricing Methods in E-Commerce (pp. 1-13). Cyprus: European Conference on Information Systems (ECIS).
  45. 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, 502-517.
  46. UN ESCAP. (2007). Single Window for Trade Facilitation: Regional Best Practices and Future Development. ESCAP, 23-26.
  47. UN/CEFACT. (2021). UNECE. Retrieved from Trade Facilitation and E-business(UN/CEFACT): https://unece.org/trade/uncefact
  48. UNCTAD. (2021). Digital Economy Report. New York: United Nations Publications.
  49. United Nations. (2021). Covid-19 And E-Commerce: A Global Review. New York: United Nations Publications.
  50. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N.,. Polosukhin, I. (2017). Attention Is All You Need. Neural Information Processing Systems, 5998 - 6008.
  51. VirtuBox. (2025, February 07 ). AI in Ecommerce: Application, Benefits and Challenges in 2025. Retrieved from VirtuBox: https://www.virtubox.io/blog/ai-in-ecommerce
  52. White & Case. (2025, March 31 ). AI Watch: Global regulatory tracker - United States. Retrieved from Whitecase: https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker-united-states
  53. Wikipedia. (2025, April 30 ). Framework Convention on Artificial Intelligence. Retrieved from Wikipedia: https://en.wikipedia.org/wiki/Framework_Convention_on_Artificial_Intelligence
  54. World Bank Group. (2022). Digitalizing SMEs to Boost Competitiveness. Washington DC: World Bank Publications.
  55. World Trade Organization. (2020). E-COMMERCE, TRADE AND THE COVID-19 PANDEMIC. Geneva: WTO Publications.
  56. Wu, Y., Schuster, M., Chen, Z., Le, Q. V., Norouzi, M., Macherey, W.,. etc. (2016 ). Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. arXiv preprint.
  57. XENA Intelligence Inc. (2024). AI in E-commerce: Applications & Use Cases in 2024. Retrieved from XENA: https://xenaintelligence.com/blog/ai-in-e-commerce-applications-use-cases-in-2024
  58. Yadav, K. (2024, August 24). AI-Driven Visual Search: Enhancing Product Discovery in E-commerce. Retrieved from Quytech: https://www.quytech.com/blog/ai-driven-visual-search-in-ecommerce/
  59. Yangyang Lu, J. Z. (2025). Balancing identity diversity and product contexts: Understanding consumer trust in AI-enhanced chatbot services. Retailing and Consumer Services.
  60. Zwass, V. (1996). Electronic Commerce: Structures and Issues. International Journal of Electronic Commerce, 3-23.
  61. Codiant. (2024, March 18). AI to Scale E-Commerce Platforms: Challenges and Solutions. Retrieved from Codiant: https://codiant.com/blog/ai-to-scale-e-commerce-platforms-challenges-and-solutions/ DHL. (2024). Logistics Trend Radar. Leipzig: DHL International.
  62. Ren, Q., Jiang, Z., Cao, J., Li, S., Li, C., Liu, Y.,. Chen, Y. (2024). A survey on fairness of large language models in e-commerce: progress, application, and challenge. New York: Cornell University.
  63. Singla, A. (2024, May 30). The state of AI in early 2024: Gen AI adoption spikes and starts to generate value. Retrieved from QuantumBlack AI by Mckinsey: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2024
  64. UNCTAD. (2021). Digital Economy Report. New York: United Nations Publications.
  65. United Nations. (2021). Covid-19 And E-Commerce: A Global Review. New York: United Nations Publications.
  66. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N.,. Polosukhin, I. (2017). Attention Is All You Need. Neural Information Processing Systems, 5998 - 6008.
  67. White & Case. (2025, March 31 ). AI Watch: Global regulatory tracker - United States. Retrieved from Whitecase: https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker-united-states
  68. Wu, Y., Schuster, M., Chen, Z., Le, Q. V., Norouzi, M., Macherey, W.,. etc. (2016 ). Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. arXiv preprint.
  69. Zwass, V. (1996). Electronic Commerce: Structures and Issues. International Journal of Electronic Commerce, 3-23.