This study examines the potential use of artificial intelligence-based chatbots (ChatGPT, Gemini, Copilot) in multi-criteria decision-making (MCDM) processes. As decision-making processes become increasingly complex, AI-supported systems have the potential to accelerate these processes and provide an objective perspective. In this context, the study focuses on the best-selling electric SUV models in the Turkish automotive market during the first ten months of 2024, namely TOGG-T10X, Tesla Model Y, KG Mobility Torres, BMW X1, Mercedes EQB, Mini Countryman, and MG. 

These models are evaluated based on various performance and cost criteria, including range, battery capacity, motor power, charging time, acceleration time, energy consumption, and price. The primary objective of this study is to compare the weight determination of these criteria using both an objective method (CRITIC) and a subjective method (LBWA), alongside the weight suggestions provided by AI-based chatbots. 

To rank the alternatives, the TOPSIS method is applied, allowing for a comparative analysis of traditional weighting methods and AI-supported decision-making approaches. This comparison aims to assess the reliability and consistency of AI chatbots in MCDM processes. The findings provide valuable insights into how AI-based systems can be integrated into MCDM frameworks, offering a new perspective on their role in decision support mechanisms. Additionally, the study highlights the advantages, disadvantages, and differences between traditional methods and AI-driven approaches in multi-criteria decision-making.