Assessing the impact of AI-generated product names on e-commerce performance

Authors

  • Oleksandr Bratus Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine https://orcid.org/0009-0003-5004-1652

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2025.1.10

Keywords:

large language models, AI-detection, e-commerce, product performance

Abstract

This paper studies the impact of Large Language Model (LLM) technology on the e-commerce industry. This work conducts a detailed review of the current implementation level of LLM technologies in the e-commerce industry. Next, it analyzes the approaches to detecting AI-generated text and determines the limitations of their application. The proposed methodology defines the impact of LLM models on the e-commerce industry based on a comparative analysis between indicators of machine-generated texts and e-commerce product metrics. Applying this methodology to real data, one of the most relevant data collected after the release of ChatGPT, the results of statistical analyses show a positive correlation between the studied indicators. It is proved that this dependence is dynamic and changes over time. The obtained implicit indicators measure the influence of LLM technologies on the e-commerce domain. This influence is expected to grow, requiring further research.

Author Biography

Oleksandr Bratus, Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv

Ph.D. student at the Department of Mathematical Methods of System Analysis of Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine.

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Published

2025-03-28

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Section

Methods, models, and technologies of artificial intelligence in system analysis and control