User Experience of Classic and AI-assisted Search Engines


  • Žiga Šolar University of Ljubljana



It is hard to imagine a world without search engines such as Google. They have become a staple in online activity as they allow an unparallel ease of access to information. The classic search engines such as Google use a word similarity-based algorithm to obtain entries from its database that are most closely related to the user query. With the rise in popularity of Generative Language Model (GLM) companies such as Microsoft have started to adopt such artificial intelligence (AI) models in combination with the classic similarity-based search engines [1], which allow both a classical method of searching for information and the conversational method seen in chatbots. This combined approach of search engines poses a question about the influence of AI on user experience (UX). Studies in the field of UX have proposed that when chatbots are introduced, humans tend to perceive them as more humanlike [2], changing the UX.

We will be looking at the UX of people interacting with classic and AI-assisted search engines. With that in mind, we will be exploring the question: “How does the UX in regard to interaction and interface design differ between the classic and AI-assisted browser search engines?”.  


We will develop multiple web applications simulating a browser. The web applications will be of two types, the classic search engine and the AI-assisted search engine. The classic search engine will follow the current UX practices, while the AI-assisted search engine will make use of both the classic search engine and chatbot UX practices.

The participants of the study will be given tasks regarding obtaining with the use of the two different tools. They will report their experience while using the tools as well as score the tools based on their UX such as usability, user-friendliness, information clarity, etc.

Results and Implications

The study is still in its infant stages, therefore data has yet to be collected. The data analysis will with identifying UX patterns and categorizing them.

The results of this study will offer an additional evidence-based approach to studying UX of people using search engines, interacting with AI and the combination of the two. Additionally, the study has the potential to bring insight to the adaptation of classic search engine optimization practices for AI-assisted search engines.


[1] "Reinventing search with a new AI-powered Microsoft Bing and EDGE, your copilot for the web," The Official Microsoft Blog, 2023. (Accessed: 8 May 2023).

[2] I. K. Haugeland, A. Følstad, C. Taylor, and C. A. Bjørkli, “Understanding the user experience of Customer Service Chatbots: An experimental study of chatbot interaction design,” International Journal of Human-Computer Studies, vol. 161, p. 102788, 2022.