Artificial intelligence (AI) has become an increasingly central component of contemporary cybersecurity practices, shaping how organizations detect threats and respond to security incidents. While existing research has largely emphasized the technical performance of AI-based cybersecurity systems, less attention has been paid to how these systems are experienced and understood by professionals in everyday organizational contexts.This study explores the role of AI in cybersecurity threat detection and incident response from an Information Systems perspective, focusing on professional perceptions,judgment, and decision-making. This qualitative study examines the experiences and perspectives of cybersecurity professionals, including analysts, engineers, and managers,regarding the use of AI-based cybersecurity systems in threat detection and incidentresponse. Using the  matic analysis, the findings show that AI primarily functions as adecision-support tool that augments human expertise rather than replacing it. Trust in AIis developed gradually and remains conditional, while AI-based cybersecurity systems influence how attention is structured and how decisions are prioritized. At the same time,responsibility and accountability remain with human actors, reinforced by organizational governance structures.The study contributes to the Information Systems field by conceptualizing AI-based cybersecurity systems as socio-technical information systems embedded within professional decision-making contexts. It also offers practical implications by highlighting the importance of human-in-the-loop approaches, calibrated trust, and governance structures for the effective and responsible use of AI in cybersecurityoperations.