Today’s digital landscape is dynamic, with new cyber threats emerging alongside new technologies, escalating business risks. Managing cybersecurity is no longer a back-office technical function, but a strategic business imperative and a board priority. Boards are not asking CISOs for just reports but to demonstrate measurable outcomes with ROI, faster MTTR, and increased productivity. All this with no increase in budgets! The C-Suite expects results that are tied to business resilience, risk posture, and efficiency.
Mounting Pressures on CISOs
CISOs across industries are concerned about the rapid evolution of the threat landscape and the mounting pressure to demonstrate security value to the business. In today’s turbulent economic landscape and shrinking budgets, the leadership demands that the CISOs quantify the impact of their security program. Security heads are faced with a new mandate to deliver AI-driven speed, efficiency, and outcomes that the board can measure. CISOs face challenges from duplicating security tools, resulting in tool sprawl that drives redundancies and operational inefficiencies. With talent shortage amidst budget constraints and capability gaps, security heads are finding it rather difficult to build more engaged and focused teams.
Limitations of the traditional SOC Models
Traditional SOCs were not built for today’s speed and scale. Alert fatigue, manual investigations, disconnected tools, and talent shortages all contribute to the operational drag. Many security leaders are stuck in a reactive loop with no clear path to improvement.
Key Challenges:
> High false positive rates
Legacy SOCs rely heavily on outdated technologies and rule-based detection, generating high volumes of alerts, many of which are false positives, leading to analyst burnout. Analysts are compelled to manually inspect and triage a deluge of meaningless signals, making the entire effort unsustainable. Regrettably, high-fidelity alerts are missed in this process.
> Siloed data and tools
Data siloes in SOCs occur when data is trapped across disconnected devices in the legacy SOC. Analysts spend significant time on manual investigation, correlating, and escalating alerts by navigating many siloed tools. Insights are found in isolation, creating barriers to rapid detection and response. Siloed data and tools also pose a challenge to an organization’s ability to enforce consistent data governance policies, leading to security vulnerabilities.
> Limited automation
Human analysts at L1 and L2 continue to interpret and triage alerts in several modern SOCs. This system cannot keep pace with the scale and complexity of modern threats. In the absence of automation, human analysts are actually a hindrance, leading to escalation backlogs and a morale crisis among SOC teams.
The longer SOCs rely on a legacy model, the more it drains money, morale, and mission readiness. Transformation to modern SOC is the only solution.
Benchmarking the SOC
Before transformation can happen, one needs to understand where one stands. This can be accomplished with key benchmarking metrics for SOC performance, such as MTTD (Mean time to detect), MTTR (Mean time to respond), case closure rates, and tool effectiveness.
Alert-to-triage ratio
This estimates how effective security monitoring tools are at filtering out the unnecessary noise and delivering the real threats to SOC analysts.
Case resolution time
Traditional SOC models often create bottlenecks, reflected in key performance metrics such as MTTR. Reducing MTTR effectively quantifies the tangible value of SOC modernization.
Percentage of automated workflows
To effectively benchmark the existing SOC, it’s essential to assess automation maturity by comparing incidents handled through automation versus manual intervention. Equally important is measuring automation’s impact on reducing MTTR.
Analyst time per incident
This serves as a standard benchmark for the time a SOC analyst spends investigating each incident. Factors influencing analysts’ time include alert volume and quality, visibility, integration of tools, and clear incident response playbooks.
Modernizing SOC with Agentic AI
Agentic AI represents the next evolution of AI-powered cybersecurity, which is modular, explainable, and autonomous. Through a coordinated system of AI agents, the Agentic SOC continuously responds and adapts to the evolving security environment in real time. It is designed to accelerate threat detection, investigation, and response by 10x, bringing speed, precision, and clarity to every function of SecOps. Agentic AI is the technology shift that changes the game. Unlike traditional automation, Agentic AI is decision-oriented, self-improving, and always operating with human-in-the-loop for oversight.
Key Advantages:
Understands context and adapts
An AI agent can act as the frontline defense against alert workload. It continuously learns from analyst feedback, behavioral baselines, and threat context to suppress irrelevant or low-priority alerts before they hit analysts’ screens.
Offloads low-level analyst work
AI agents can offload specific, repetitive tasks from analysts across every level of the SOC. These decision-capable entities have real operational responsibilities, allowing human analysts to focus on higher-value work that requires judgment, creativity, and strategy.
Speeds up detection and response
This Agentic AI is capable of accelerating threat detection, investigation, and response several times over, bringing speed, precision, and clarity to every function of SecOps. The agents elevate SOC teams and do not replace them.
Surfaces what matters most
AI agents do not overwhelm analysts with a flood of alerts, but they filter noise, investigate anomalies, triggering automated responses and highly critical threats only so security teams can focus only on high-impact tasks.
Demonstrating ROI to the Board
Modernizing the SOC is about leveraging better technology and achieving greater business value. CISOs are expected to align with the organization’s business strategy while defending the budget. They should leverage technologies that enable meaningful measurement and confident reporting, linking results to ROI and providing executive dashboards for a clear view of security outcomes. Key metrics should include a reduction in MTTR, a decrease in analyst hours per incident, fewer false positives reaching senior staff, faster risk mitigation, and overall gains in platform efficiency.
Redefining what a modern SOC can be means shifting perspectives with confidence, seeing it not merely as a cost center but as a strategic asset. Powered by agentic AI and guided by human oversight, the modern SOC evolves into a true source of competitive advantage.