Role of Artificial Intelligence in Data-Infrastructure Vulnerability Management

Abstract

This article examines the role of artificial intelligence in managing vulnerabilities across data infrastructures. It describes the methods used to identify, analyse and remediate weaknesses, as well as the difficulties encountered during deployment. The purpose of the study is to evaluate how AI is applied to data-security tasks and to assess its capabilities and limitations. A review of academic publications, risk-management models and publicly available information on cyber-attacks provides a broad perspective on the topic. Algorithms for monitoring network activity, forecasting threats and automating vulnerability remediation are discussed. Findings show that AI accelerates remediation processes by handling large data volumes and adapting to shifts in the threat landscape. Persistent challenges include data-quality issues, ethical risks and the possibility that the technology could be misused for illegal purposes. The need for robust, transparent models that resist manipulation is underscored. The material will benefit cybersecurity professionals, AI developers, IT managers and researchers who focus on the ethical aspects of new technologies.