Artificial intelligence implementation in data protection of Russian companies

Abstract

The article examines the application of artificial intelligence in cybersecurity, focusing on the experience of Russian companies. The study analyzes artificial intelligence technologies used for threat detection, vulnerability assessment, and automation of information assets protection processes. The aim of the article is to evaluate practical implementations of artificial intelligence in cybersecurity and assess its effectiveness. The research explores key areas including abnormal activity detection, phishing attack prevention, and incident response automation while examining case studies from major Russian corporations such as Sberbank and Rostelecom. The methodology relies on the analysis of open data, publications, and reports. The author’s approach emphasizes the Russian context, revealing unique aspects and challenges of artificial intelligence adoption in local cybersecurity practices. The novelty of the research lies in summarizing the data on artificial intelligence applications in the Russian cybersecurity and identifying its key benefits and challenges. The results of the study demonstrate successful artificial intelligence implementations in banking, telecommunications, and government sectors. While confirming significant improvements in cybersecurity effectiveness through artificial intelligence, the research also highlights persistent issues such as false positives and ethical concerns. Future research directions include automation advances and closer integration of artificial intelligence technologies into cybersecurity systems