Pharmacovigilance involves the intake, processing, and evaluation of adverse events associated with pharmaceutical products, with the aim of enhancing understanding of their safety profiles and supporting the ongoing assessment of their benefit–risk balance. This article explores signal management in pharmacovigilance, covering the process from detection to action implementation. Signal detection is typically performed by safety scientists using qualitative and quantitative methods. Validated signals undergo thorough assessment, and confirmed signals may lead to regulatory actions such as label updates or market withdrawal. Traditional methods are challenged by growing data volumes, prompting the adoption of artificial intelligence techniques. Despite promising results, regulatory gaps highlight the need for harmonised frameworks to fully leverage artificial intelligence while maintaining ethical standards.