The average company’s SOC receives 10,000 alerts per day. Each requires 20 to 40 minutes to properly investigate, but even fully staffed teams can only handle 22%. More than 60% of security teams admitted to ignoring alerts this later proved critical.
Running an effective SOC has never been more difficult, and now the work itself is changing. Tier 1 analyst tasks like sorting, enrichment, and escalation are becoming software functions, and more SOC teams are turning to supervised AI agents to handle the volume. Human analysts shift their priorities to investigate, review, and make extreme decisions. Response times are reduced.
However, failing to incorporate human insight and intuition comes at a high cost. Gartner predicts more than 40% of agentic AI projects will be canceled by the end of 2027, with the main drivers being unclear business value and inadequate governance. Better manage change and ensure generative AI does not become a problem agent of chaos in SOC are even more important.
Why the old SOC model needs to change
Burnout is so severe in many SOCs today that senior analysts considering career changes. Legacy SOCs that have multiple systems issuing conflicting alerts and many systems that can’t communicate with each other at all make work a recipe for burnout, and the talent pipeline can’t fill up any faster than burnout empties it.
Documents from CrowdStrike’s 2025 Global Threats Report pause times as fast as 51 seconds and found that 79% of intrusions are now malware-free. Attackers instead rely on identity theft, credential theft, and living off the land techniques. Manual triage designed for hourly response cycles cannot compete.
Like Matthew Sharp, CISO at Xactly, told CSO Online: "Adversaries are already using AI to attack at machine speed. Organizations cannot defend against AI-based attacks with rapid responses."
How limited battery life reduces response times
SOC deployments that compress response times share a common pattern: limited autonomy. AI agents automatically handle sorting and enrichment, but humans approve containment actions when severity is high. This division of work processes alerts volume at machine speed while retaining human judgment on decisions that carry operational risk.
Graph-based detection changes the way defenders perceive the network. Traditional SIEMs display isolated events. Graph databases show the relationships between these events, allowing AI agents to trace attack paths instead of sorting through alerts one by one. A suspicious login looks different when the system understands that the account is two hops away from the domain controller.
Speed gains are measurable. AI reduces threat investigation times while increasing the accuracy in relation to the decisions of lead analysts. Separate deployments show that AI-driven sorting achieves over 98% agreement with human expert decisions while reducing manual workloads by over 40 hours per week. Speed means nothing if accuracy decreases.
ServiceNow and Ivanti signal broader shift to agentic IT operations
Gartner predicts that multi-agent AI in threat detection will move from 5% to 70% of implementations by 2028. ServiceNow spent approximately 12 billion dollars on securities acquisitions in 2025 alone. Ivanti, which compressed a three-year roadmap for core hardening in 18 months When nation-state attackers validated the urgency, they announced agentic AI capabilities for IT service management, bringing the limited autonomy model reshaping SOCs to the service desk. Customer preview will launch in Q1, with general availability later in 2026.
Workloads that disrupt SOCs also damage service desks. Robert Hanson, CIO of Grand Bank, faced the same constraint that security executives are familiar with. "We can provide 24/7 support while freeing up our service desk to focus on complex challenges," Hanson said. Continuous coverage without proportional staffing. This result is driving adoption in financial services, healthcare and government.
Three governance boundaries for limited autonomy
Limited autonomy requires explicit governance limits. Teams must specify three things: which categories of alerts agents can act on autonomously, which require human review regardless of confidence score, and which escalation pathways apply when certainty falls below the threshold. High severity incidents require human approval prior to containment.
It is essential to establish governance before deploying AI in SOCs if an organization wants to benefit from the time and containment benefits that this latest generation of tools has to offer. When adversaries use AI as a weapon and exploit CVE vulnerabilities Faster than defenders react, autonomous detection is becoming the new challenge for remaining resilient in a world of zero trust.
The way forward for security leaders
Teams should start with workflows where failures are recoverable. Three workflows consume 60% of analyst time while providing minimal investigative value: phishing triage (missed escalations can be detected in secondary review), password reset automation (low blast radius), and malfunction indicator matching (deterministic logic).
Automate them first, then validate accuracy against human decisions for 30 days.
