Oleksandr Yeroshkin, Janusz Sobecki
In the world of dynamic e-commerce, competition is fierce, and the ability to attract and retain customers is becoming crucial. In this reality, adaptive user interfaces (UI) play an important role, allowing e-commerce platforms to personalize the shopping experience to better understand and meet customer needs. When combined with advanced artificial intelligence (AI) technologies, adaptive UI can bring revolutionary changes to the way customers interact with e-commerce platforms. In this article, we will discuss how AI can be used to design and improve adaptive user interfaces in e-commerce systems, and what benefits can result from this combination. © 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ([https://creativecommons.org/licenses/by-nc-nd/4.0](https://creativecommons.org/licenses/by-nc-nd/4.0)) Peer-review under responsibility of the scientific committee of the 28th International Conference on Knowledge Based and Intelligent information and Engineering Systems Oleksandr Yeroshkin et al. / Procedia Computer Science 246 (2024) 2874–2881 2875 tion of an experimental approach in a controlled environment. During the implementation and verification phases, we will be able to generate alternative solutions and evaluate them according to the UX and/or conversion requirements. The paper is structured as follows. In the second section, the state of the art is presented. Then, in the following section, an example of a commercial system whose user interface will be adapted is given. In the fourth section, the proposed solution of adapted UI based on AI is described. In the final section, we summarize the paper and give some information on the proposed future work. 2. State of the art In the beginning, UI recommendation services did not use artificial intelligence methods [12]. According to Baraglia [4] and Kopel [10], mainly traditional approaches were used at that time. However, currently we are dealing with solutions that intensively use various AI algorithms. Automating user interface optimization can be achieved using a variety of techniques based on both traditional ap- proaches and AI and machine learning (ML) algorithms. When it comes to optimizing user experience in e-commerce, there are three approaches: adaptable, semi-adaptive, and fully adaptive [1]. The first involves manual adjustment by a user or expert according to their usage criteria [18]. The second involves manual adjustment supported by system recommendations which is a kind of evol