Generative Artificial Intelligence (GenAI) has shown tremendous potential in the field of education and especially in the field of Mathematics. So far, there is a plethora of GenAI-based tools available in Mathematics that have been extensively used and evaluated by academics and users. However, due to the plethora of available tools there is some doubt among the users and academics as to which GenAI tools are considered reliable, effective and appropriate for different levels and topics in the field of Mathematics. Based on the existing literature, the present study aims to provide a critical evaluation of how educators, students and the academic community perceive the usability and performance of popular artificial intelligence (AI) applications for mathematics education, in relation to the ability to improve learning outcomes. The aim of the study is to answer the research question: What are the perceptions of academics, educators, and students on GenAI applications in Mathematics?. This study focuses on typical GenAI tools in the field of Mathematics such as Mathos AI, MATHia, Wolfram Alpha, Mathful, Photomath, AI Math Coach, MathGPT pro and Symbolab providing a critical evaluation by academics and users in order to examine the usefulness, usability and performance of these tools. Specifically, we employed a qualitative research methodology which involves a critical evaluation of findings derived from the academic literature and existing reviews from users. This methodology ensures the in-depth analysis and discussion of these tools as academics and users have a significant impact on the use and implementation of these GenAI tools. The results of the study provide a meaningful and useful feedback to educators, students, researchers and to companies producing AI tools, in relation to the effective application of GenAI tools in the field of mathematics. The overall conclusions derived from this study indicate that both academics and users agree that these specific GenAI tools are useful for solving mathematical problems while users complement the academics' views by providing information about the limitations of the GenAI applications.

Keywords: Generative AI, Mathematics, Applications, Critical Evaluation.