This paper presents a bibliometric review of scientific publications indexed in the Web of Science databases that investigate the use of Artificial Intelligence (AI) in cybersecurity. The study aims to identify the most active authors in the field, the institutions funding research on AI applications in cybersecurity and their main subdomains, as well as the level of documentation of published studies. The study focuses on three major pillars: biometric security, the detection and defense against social engineering, and ethical and privacy implications. The data were extracted and analyzed using a Python script, assessing the total number of published articles, the most influential authors, their affiliated institutions, as well as editorial characteristics such as the average number of pages and the average number of references used annually. The results highlight the continued growth of academic interest in the application of AI in cybersecurity, emphasizing the areas where the greatest research investments are being made and where the most significant challenges arise, including issues related to bias, data privacy, and the robustness of AI models. This analysis provides a coherent picture of current and future research directions, highlighting both the potential of AI and the limits and risks associated with its use.