Your AI Agents Are Ready. Your SOC Isn't.

Matt Marshall raised a critical point earlier today on the Agentic Infrastructure Gap, and how the biggest misconception in enterprise AI today is thinking the agent is the product. It isn’t. As he noted, “The agent is just the engine. The enterprise-grade chassis—the security, governance, and orchestration protocols—is still being invented.” Securing agentic AI at scale is one of the most important conversations happening at VB Transform (https://lnkd.in/gGA67_fm), VentureBeat 's enterprise AI event taking place next week in San Francisco on June 24-25.

CISOs are unprepared for new, proliferating threat surfaces

The numbers paint a stark picture that should alarm every CISO immediately. While 97% of cybersecurity professionals fear their organizations will face AI-generated security incidents, Gartner found that only 15% believe their current cybersecurity tools can detect and stop AI-generated threats. This isn't merely a technology gap; it's a fundamental architectural mismatch between yesterday's security operations and tomorrow's threat landscape.

Enterprises have rapidly adopted generative and agentic AI. Yet, their Security Operations Centers remain anchored to legacy detection methods that are incapable of matching AI-driven attacks, which evolve quickly, operate autonomously, and exploit vulnerabilities with surgical precision.

The statistical reality of SOC obsolescence

The disconnect between AI adoption and SOC readiness reveals itself through compelling data. According to Gartner's 2024 Designing and Building Modern Security Operations Survey, only 57% of security operations metrics effectively drive cybersecurity decision-making, while 46% of security professionals spend more time maintaining tools than defending their organizations. More troubling, 78% of CISOs report that AI-powered cyber threats already significantly impact their organizations, a 5% increase from the previous year.

Legacy SOCs struggle fundamentally because they depend on rule-based detection, reactive incident management, and manual alert triaging, processes that collapse when attackers leverage AI's speed and adaptability. These operations centers face increasing Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) when confronting AI-scale attacks, with traditional monitoring methods consistently falling behind evolving threat capabilities.

Critical attack vectors: Prompt injection and API exploitation

The emergence of prompt injection attacks exemplifies why traditional Security Operations Centers (SOCs) often fail against AI-enabled threats. These attacks exploit the fundamental openness of large language models to subtle manipulation, achieving unauthorized disclosure without triggering conventional detection systems. Simultaneously, 40% of all phishing emails targeting businesses now rely on AI-generated content, yet 60% of recipients still fall victim, equivalent to the rates for traditional phishing.

APIs integrating AI agents with backend systems represent another critical blind spot. Gartner's SIEM-centric SOC Reference Architecture emphasizes that visibility into API-driven data flows remains essential yet often neglected in legacy SOC designs. This oversight creates dangerous vulnerabilities where stored prompt injection attacks embed malicious prompts in training data, influencing AI output when accessed later.

SOC maturity and performance metrics

Gartner's research reveals why legacy architectures consistently struggle to keep pace with advanced threats. The Expanded SOC Model defines four essential functions: threat intelligence, exposure assessment and validation, threat detection and incident response, and response and impact avoidance. However, most legacy SOCs focus heavily on reactive alert management without sufficient investment in proactive threat hunting or exposure validation capabilities.

Modern SOC effectiveness requires sophisticated metrics beyond traditional alert clearance volume. Key performance indicators must evolve to measure Mean Time to Contain (MTTC) and Mean Time to Engage (MTTEngage), delivering greater accuracy in identifying potential threats. Advanced SOCs track threat hunting frequency, exposure validation coverage, and predictive threat identification, the core metrics that require data integration for reliable accuracy as table stakes. Legacy SIEM platforms were not designed with those advanced capabilities and can't provide their depth of insights.

The Hybrid SOC imperative

Scaling up a SOC with only internal staff proves difficult, if not impossible, for most organizations. Successful modern SOCs adopt hybrid models, leveraging internal staff for strategic threat management while outsourcing routine threat detection and response to external providers. This approach addresses the critical skills shortage, where the global cybersecurity workforce gap exceeds 4 million positions.

The six foundational roles every SOC requires include: SOC Manager for strategic oversight, Level 3/Senior Analysts for complex investigations, Level 1/2 Junior Analysts for alert pipeline management, Content Engineers for detection capability design, Threat Experts for intelligence analysis, and Engineers for operational tool maintenance. Organizations must strategically balance these roles between internal teams that handle sensitive, strategic functions and external providers that manage tactical, high-volume operations.

Detection stack modernization starts with the data

Legacy SIEMs were not built for today’s threat landscape. Schema limits, storage bottlenecks, and rigid rule engines are now directly responsible for more than half of all detection gaps. That is a structural problem. Modern detection stacks need a broader view. Endpoint data alone is not enough. SOC teams and the security leaders managing them require identity signals, network flow, and cloud telemetry to collaborate in real-time and identify AI-driven attacks.

XDR and detection as a service are helping teams scale correlation and reduce blind spots. But no tool can compensate for poor alignment. Detection programs must focus on point of attack, method of detection, and alert quality to ensure the signals support real risk-based decisions.

Operational excellence starts with the right metrics

Every SOC lead and their teams I've ever met are obsessed with measuring performance and looking for new ways to excel at what they do. The challenge many face is that measurement without maturity creates more confusion than clarity. From conversations and visits across dozens of SOCs this year, it's clear that metrics must align with SOC maturity. Tracking too much too early can overwhelm teams and stall progress, while mature SOCs use focused metrics to drive consistent, month-over-month results.

But none of it works without context. Metrics without baselines are like driving down a highway without headlights. Every SOC needs a straightforward method for building baselines and using them to communicate risk, performance, and improvement to the business.

Rebuilding the SOC for an AI-native threat landscape

No enterprise can afford SOCs locked into legacy methods when 93% of businesses expect daily AI attacks over the next year. Modernization requires comprehensive architectural transformation beyond incremental tool updates. Success depends on aligning SOC objectives with strategic business needs, integrating real-time analytics capabilities, enhancing proactive threat detection, and carefully balancing internal versus external SOC roles.

The statistics make the need for urgency clear: organizations that delay SOC modernization risk falling behind adversaries who have already weaponized AI for sophisticated, autonomous attacks. The SOCs that will succeed embrace transformation now, building capabilities that evolve with the threat landscape rather than simply reacting to it.

Modernizing security operations means building capabilities that can detect and respond to threats at the speed of AI. This is not just an upgrade. It is a strategic shift. The gap between the speed at which attackers move and the speed at which defenders respond is widening. Without decisive action, that gap becomes a permanent disadvantage.