This paper conducts a comparative bibliometric analysis to evaluate the role of AI in cybersecurity risk management. Using two distinct datasets from Scopus, one with a broad focus on AI and cybersecurity, and the other specifically targeting risk management, the study identifies trends, key contributors, and emerging topics in the field. The findings highlight the complementary nature of the two approaches, with the broad query providing a comprehensive overview and the focused query delivering precise insights into risk management strategies. The paper also discusses the dominance of neural networks in AI models, the prevalence of threats like computer crime and DOS attacks, and the growing importance of sectors such as finance and healthcare in cybersecurity research.