This study uses the Analytic Hierarchy Process (AHP) methodology to compare three functional testing tools of AI-based software: Selenium, Testim, and Applitools. The goal is to evaluate these tools based on six key criteria: usability, error detection efficiency, integration with other systems, technical support, cost, and flexibility. Each criterion is divided into specific sub-criteria, with weights assigned to quantify the performance of each tool. The evaluation criteria are established through an exhaustive literature review and expert consultations, and a hierarchy is organized to ensure a detailed and quantitative assessment of each tool. The results show that Testim receives the highest scores, excelling in usability, problem-solving efficiency, and technical support with a total score of 0.84. Applitools got a total of 0.82 and its best features were integration and error detection. While Selenium got the lowest score of 0.75, it is recognized for its flexibility and cost but it needs to improve its usability and technical support. This study provides an impartial framework for selecting AI-based software functional testing tools, highlighting the importance of considering multiple criteria in decision-making. The results benefit projects aiming to improve software quality by choosing the tools that best meet their needs.