Security teams are good at spotting threats. Acting on them fast is the harder problem.
Over the years, security teams have honed their expertise at detecting threats. But the deluge of tens of thousands of alerts from a multitude of devices spread across the organization makes it difficult to detect the real threats and respond accordingly, says Mike Plavin, senior technical product marketing manager at ServiceNow.
Simply detecting a threat is not enough; teams have to decrease remediation response time through an auditable trail of actions. AI can help.
Improving alert response time
The clock might start the moment an alert fires, but manual processes slow both prioritization and response to critical incidents. AI for prioritization is just as critical as response. Triaging alerts, gathering context, routing tickets, notifying stakeholders, and documenting every action is not only busywork that burns up analyst time but is critical to make sure the team is focused on the right incident with the correct response. To complicate matters, attending to the finicky playbook details leads to analyst burnout, adversely affecting the decisions where real expertise is needed.
When an incident escalates into a crisis event, delays can compound problems because data and teams are siloed: the detection lives in one stack, the response is handled by another team, and the connections between security, IT, risk and other teams (like HR, Legal, and OT Operations) are handled by swivel chair and email.
Manual process latency is a real threat multiplier
The latency caused by manual processes multiplies quickly. “The most consequential delay that occurs after an alert fires is the gap between when the alert is determined to be a true positive and the time to resolution,” Plavin says.
Every wasted minute between threat detection and remediation can increase the extent of lateral movement and data exfiltration, thereby expanding the blast radius.
Security orchestration, automation, and response (SOAR) emerged as a way to address the many remediation tasks. But rule-based automation is not the same as AI. It can execute simple “if-then” commands, but SOAR struggles to reason, adapt, or handle novel situations. If any threat deviates from routine ones, the analyst still has to intervene and determine what to do next to close the gap manually.
It need not be this way. Agentic incident response (AIR) can help.
What agentic incident response can do
To reduce time to prioritize and remediate, agentic incident response helps sift through the deluge of threats to identify the real ones and quickly add risk context, so analysts know which to address first.
In AIR scenarios, all alerts route to a zero-touch alert triage workspace, where a third-party AI SOC tool deflects the false positives before the analyst ever sees them. In addition, once the true positives are promoted to security incidents, AI agents triage them, enriching them with context, risk scoring, and prioritization, executing playbook steps, documenting actions, and coordinating cross-team actions automatically.
Guardrails, approval gates, and audit trails integrate into the architecture to establish clear rules that AI agents must follow while keeping the human in the loop. Analysts still act on threats that could have serious consequences.
By strategically wading through the haystack and prioritizing the threats analysts need to attend to, AIR makes remediation proactive rather than reactive.
Context adds intelligence to remediation response
Better outcomes don't rely solely on faster reactions to threats. Instead, adding context makes remediation more intelligent. “Context adds business criticality, which is one of the most important aspects of cybersecurity,” Plavin says, “it’s not just about a bad thing happening; it matters who or what it happened to and what other things they have access to.”
The approach is especially relevant given the expansion from IT into OT and IoT, which increases the attack surface area. Worse, OT environments play by different rules, with distinct communication protocols, risk tolerances, and regulatory requirements.
AIR adds asset context from identity and permissions data, threat intelligence, historical incident data, CMDB-derived asset context, and OT-specific signals for industrial environments. Given the vast IT-OT estate, understanding context is everything.
What success looks like
As the volume of threats increases, hiring more security analysts fails to address the underlying problem: there are too many manual protocols in remediation, wasting expertise. Teams using AIR become more efficient and expert at handling the scale of threat remediation without adding headcount. They do all this while enabling security analysts to focus on more proactive and critical cybersecurity projects.
In turn, success with an agentic incident response program is measured by reductions in triage and containment times and by analyst workloads shifting from routine orchestration tasks to judgment.
The value of AIR
Much of the preliminary response to a valid and identified threat follows a standardized playbook. Manually checking off these tasks takes time and delays response time. Worse, it wastes one of a security team’s most valuable resources: analyst expertise. When done right, AIR delivers faster containment of real threats, less analyst burnout, and a comprehensive audit trail from threat detection through remediation and closure.
Agentic incident response is the best-of-all-worlds approach to cybersecurity, where AI owns the workflow and analysts own the decisions.
Explore agentic incident response solutions from ServiceNow.
