From Function-Centric AI to Continuous Cyber Resilience: Exploring Agentic AI for Adaptive and Quantum-Ready Cybersecurity
Artificial Intelligence (AI) has become a key enabler of modern cybersecurity, driving advancements across Security Operations Centers (SOC), Incident Response (IR), Threat Intelligence, Identity and Access Management (IAM), Cloud Security, and Governance functions. However, current AI adoption remains largely function-centric, with capabilities primarily deployed to optimize individual cybersecurity domains and address localized operational challenges. While these implementations improve efficiency, detection accuracy, and decisionmaking, they often operate in isolation, limiting the ability of organizations to connect knowledge, context, and experience across the broader cybersecurity landscape.
This research explored the potential evolution from function-centric AI adoption toward a holistic, continuously learning cybersecurity ecosystem enabled by Agentic AI. Rather than viewing Agentic AI solely as a tool for automation, the research examined its potential role as a connective intelligence layer capable of correlating information across cybersecurity functions, preserving organizational knowledge, identifying overlooked relationships, and providing contextual awareness that extended beyond individual teams, processes, and technologies. Within this perspective, Agentic AI augmented human expertise by helping security professionals recognize patterns, dependencies, and risks that might otherwise have remained hidden within operational silos, fragmented data sources, and accumulated institutional knowledge.
The research further examined how a holistic Agentic AI approach could strengthen organizational adaptability and long-term cyber resilience. While cybersecurity programs were primarily designed to address present-day threats, emerging challenges such as quantum computing and the transition to Post-Quantum Cryptography (PQC) were often managed as separate strategic initiatives. This separation created visibility gaps in cryptographic assets, dependencies, and migration readiness. By continuously learning from operational activities, architectural knowledge, risk assessments, and historical decisions, Agentic AI presented the potential to bridge the divide between current security operations and future-readiness efforts.
The next evolution of cybersecurity may extend beyond making individual security functions more efficient toward enabling them to continuously learn from one another. As Agentic AI becomes increasingly capable of correlating knowledge, identifying overlooked relationships, and connecting present-day operations with future risks, new opportunities emerge to rethink how cybersecurity organizations learn, adapt, and prepare for change. In particular, the growing need for quantum readiness raises a broader question: can a holistic application of Agentic AI help transform cybersecurity from a collection of optimized functions into an ecosystem capable of continuously evolving alongside the technologies and threats it seeks to defend against?
Felissa Mariz D. Marasigan – KPMG R.G. Manabat & Co.
Felissa Mariz Marasigan is a cybersecurity professional with eight years of experience in malware analysis, reverse engineering, security operations, and incident response. Her work spans complex threat investigations, CSIRT operations, and security automation, bridging deep technical expertise with the evolving demands of modern cyber defense. With a keen interest in emerging technologies, particularly agentic AI and next-generation security capabilities, she explores how innovation can strengthen cyber resilience and transform the way organizations detect, investigate, and respond to threats.
Mark Gabriel Rizare – KPMG R.G. Manabat & Co.
Mark Gabriel is a cybersecurity professional with years of experience in Security Operations Center (SOC) environments, specializing in threat monitoring, threat detection, incident investigation, incident response, threat hunting, and security rule tuning. He has extensive experience analyzing security events, identifying malicious activity, investigating potential threats, and enhancing detection capabilities through the continuous optimization of security monitoring use cases and alerting mechanisms. He is proficient in leveraging SIEM and security platforms to strengthen cyber defenses, improve threat visibility, and enhance organizational security. His experience spans network security monitoring, log analysis, and the investigation of sophisticated security incidents across enterprise environments. He has a strong background in threat hunting, security monitoring, incident analysis, and developing actionable recommendations that help organizations improve their detection and response capabilities.