The Obsession with Speed
When people talk about applying AI in the Security Operations Center (SOC), the conversation almost always starts with speed. The common comparison goes something like this: “What takes a human analyst 45 minutes, an AI agent can do in 2 minutes and 45 seconds.”
That’s true, and speed does matter. But it’s hardly the most valuable metric. If speed is all we measure, we miss the bigger transformation AI is bringing to the SOC: the ability to execute investigations with coverage and consistency at a scale that humans simply can’t match.
The Human Baseline
SOC analysts are under relentless pressure. They face high alert volumes, fatigue from repetitive tasks, and the constant threat of burnout. Under these conditions, human investigations often suffer from:
- Limited coverage — shortcuts are taken, or alerts are dismissed, just to keep pace. Lower-priority alerts in particular often become “second-class citizens,” pushed aside because the team simply doesn’t have capacity. Yet these alerts can be early symptoms of much larger issues that only become obvious when the problem escalates. By the time it’s visible, it’s often too late.
- Inconsistency — the same alert might be handled differently depending on the analyst, shift, or workload.
- Missed evidence — enrichment steps are skipped, indicators are overlooked, or escalation comes too late.
This variability creates blind spots that attackers can exploit.
Why Comparing “AI Time” to “Human Time” Misses the Point
It’s tempting to frame AI as simply faster humans. But AI agents don’t work in shifts, get tired, or cut corners when the queue is long. They execute workflows exactly as prescribed, every time.
The “speed story” is easy, but it’s shallow. The real value lies in coverage – ensuring every alert is investigated thoroughly – and consistency – ensuring every investigation follows the same reliable process.
The Value of Coverage
Coverage means nothing gets missed. Every alert, every enrichment, every escalation step in a procedure is executed — even when the workload spikes. Instead of treating alert surges as an unsolvable staffing problem, AI reframes them as a load balancing problem — the kind of challenge modern SaaS platforms have already solved at scale.
Example: In a phishing investigation, coverage ensures that the process doesn’t stop at a domain reputation check. The AI agents always correlate across endpoints, network logs, and threat intel feeds. This captures the same thoughtful thoroughness a human investigator would apply, but packages it into scalable software. That breadth reduces blind spots and ensures attackers don’t slip through the cracks.
The Value of Consistency
Consistency doesn’t mean every investigation follows a rigid, identical path. It means the quality of the investigation is reliable — regardless of alert type, time of day, or workload.
Humans bring variance — two analysts triaging the same alert may take different paths and reach different conclusions. AI agents, by contrast, maintain consistency in outcomes while dynamically adapting the investigation path based on context and data. This ensures:
- Fewer errors and missed steps.
- Predictable levels of quality across shifts, teams, and geographies.
- Stronger compliance and audit reporting, since every investigation aligns with policy.
When investigations are both broad in coverage and consistent in quality, SOC leaders can finally trust that every alert is treated with the same level of rigor — without sacrificing the adaptability needed to meet dynamic threats.
Measuring Metrics That Define AI Success
Metrics like MTTD and MTTR will always matter, but they aren’t sufficient on their own. They measure speed, not quality. To capture the true value of AI in the SOC, we need to also measure:
- Coverage Rate — % of alerts fully investigated.
- Consistency Index — variance in how similar alerts are handled.
- Error Reduction — fewer missed IOCs, misclassifications, or policy violations.
- Auditability — % of investigations that can be fully reconstructed from logs without gaps.
These metrics reflect outcomes that directly reduce organizational risk — outcomes speed alone cannot guarantee.
Conclusion: Redefining SOC Metrics in the AI Era
Speed is the easy story, but it’s not the most important one. The AI SOC should be measured by coverage and consistency.
When every alert gets investigated fully, when every step is executed the same way every time, and when every action is logged and auditable — you not only respond faster, you respond better.
That’s the real promise of AI in the SOC: not just doing things quicker, but doing them right, every single time.
