In today’s rapidly evolving digital landscape, the role of incident response for cybersecurity teams is undergoing a profound transformation. Previously, cybersecurity incidents predominantly stemmed from external attacks or insider threats orchestrated by human actors. The Gartner Cybersecurity and Risk Management Summit 2026, held in National Harbor, Maryland, highlighted this shift, showcasing insights from analyst Craig Porter. He articulated a critical emerging trend: the increasing occurrence of unintended incidents generated by internal AI agents, necessitating a reevaluation of how Chief Information Security Officers (CISOs) and their teams respond to security challenges.
According to Porter, a staggering 80% of unauthorized AI-related transactions arise from internal violations of enterprise policies. These violations often relate to instances of information oversharing, inappropriate use of AI, or simply misguided AI behavior. This revelation underscores the pressing need for organizations to understand and address the complexities introduced by AI technologies in their cybersecurity frameworks.
Porter identified three significant challenges that Gartner consistently observes within organizations when navigating this landscape. First, there is a lack of a universally accepted definition of an AI incident. Situations may arise from various factors like model drift, prompt injection, and the operation of autonomous agents that carry out functions they were not originally designed to execute. This ambiguity complicates efforts to effectively manage and mitigate such events.
Second, many risks associated with AI behaviors are often hidden from the view of Security Operations Centers (SOCs). The inherent complexity of AI systems may place significant risks beyond the traditional perimeter of oversight that organizations have established.
Lastly, the nature of incidents is changing so rapidly that traditional reactive measures are no longer sufficient. Porter argued that AI operates at a pace that can outstrip the investigative capabilities of security teams—by the time a team begins to assess a situation, AI may have already made thousands of decisions autonomously.
Porter’s session emphasized a dynamic new role for CISOs as their responsibilities are in constant flux, paralleling the evolution of the threat landscape. AI technology has significantly expanded the capabilities of systems, but this also raises new challenges unique to the digital age. Porter advocates for the overhauling of incident response protocols to integrate AI’s intricate role in cybersecurity.
A key component of this reevaluation is the necessity for organizations to define or redefine the taxonomy of AI incidents. With an ever-increasing array of events fueled by AI, it is crucial that organizations establish a clear framework regarding what constitutes an AI-related cybersecurity incident. Porter noted that organizations often struggle to categorize these emerging threats due to their complex and blurry boundaries. Expanding existing taxonomies is essential; it must now incorporate AI-specific risks such as prompt injection, data poisoning, model bias exploitation, and the challenges presented by deepfake technology.
Furthermore, organizations are urged to evolve their incident response playbooks to reflect this expanded understanding. Dedicated roles focused on navigating the complexities of internal risks, third-party threats, and external AI incidents will be essential.
Transitioning from a reactive to a more resilient incident response strategy is vital, as Porter emphasized. His assertion that “the key takeaway here is that traditional incident response no longer scales” resonates deeply within the context of AI integration. The process now necessitates an investigation not merely focused on incidents, but on understanding the underlying behavior, design, and decision-making processes of AI applications.
In this AI-centric era, incident response teams must operate under predefined escalation protocols that reflect both regulatory and technical severity. This includes the establishment of clearly defined restoration processes and the adoption of metrics specifically tailored to monitor AI systems. Additionally, cross-functional collaboration will be essential, with representation from legal, compliance, human resources, and business owners in triaged response efforts.
As AI behavior is dynamic, Porter emphasized that oversight must also be continuous rather than dependent on periodic checks. This calls for comprehensive logging of AI transactions and the implementation of rigorous third-party controls. Through enhanced observability—incorporating elements such as model and system artifacts, behavior evidence, and telemetry—security teams can better navigate the complexities of AI risks.
In sum, the era of AI requires a fundamental reevaluation of what constitutes a cybersecurity incident and how it should be approached. With many risks emanating from authorized AI models, proactive preparation is essential. Regular cross-functional training, tabletop exercises, disaster recovery planning, and business continuity strategies must become integral components of organizational readiness.
As Porter astutely observed, “There may be no attacker here. The system is behaving as authorized, yet it still creates risk.” This paradigm shift in understanding risk highlights the urgent need for organizations to adapt and fortify their cybersecurity strategies within the AI landscape, ensuring they are equipped to face the challenges of a complex and evolving digital environment.