Old SOC vs New SOC: Stop Drowning in Countless Alerts

TL;DR

Traditional SOCs drown analysts in manual triage, while AI-powered attacks move at machine speed. 92% of healthcare organizations were breached in 2024, with losses over $500,000 jumping 400%. Secure.com’s Digital Security Teammates automate the operational grind, delivering 70% less manual work and 45-55% faster responses while analysts focus on critical thinking.

Introduction

The Old SOC is dead.

For 17 days in July 2024, McLaren Health Care experienced a devastating breach, hackers moved freely through its Michigan hospital systems, stealing Social Security numbers, medical records, and health insurance data from 743,131 patients while its traditional SOC failed to detect it. By the time they detected the breach on August 5th, the damage was done.

This story repeated itself across hundreds of healthcare facilities in 2024, all victims of traditional security operations that react too slowly, drown in false alerts, and discover breaches only after patient data is stolen.

Key Takeaways

Traditional SOCs are failing: Most healthcare orgs experienced cyberattacks in 2024, with losses exceeding $500,000
Manual triage is the bottleneck: Analysts spend most time on mechanical work (gathering context, tool-switching, documentation) instead of actual security analysis
AI attacks are outpacing defenses: 442% surge in phishing attacks, with over 60% of organizations unprepared for AI-powered cyber threats
Digital Security Teammates change the equation: Automated triage, evidence gathering, and 24/7 operations let humans focus on decision-making
Measurable impact: Organizations report a 70% reduction in manual work and a 45-55% faster incident response
Trust through transparency: Every teammate's decision includes documented reasoning, making AI output verifiable and audit-ready

The Death Spiral of Traditional SOCs

Here's the problem with how most security teams operate today: your analysts spend the majority of their time not on security analysis, but on the mechanical work that must be done before analysis can even begin.

Alert triage. Context gathering. Evidence collection. Cross-referencing data across multiple systems. Documentation. The actual investigation and decision-making? That's a fraction of their day.

The worst part is managing tons of AI-backed attacks with a lean SOC team using SOAR solutions that require customization and comprehensive playbook development. Healthcare organizations face losses exceeding $500,000, a figure that jumped 400% from 2024 to 2025.

Yet, over 60% of organizations remain unprepared to fight against AI-powered cyberattacks.

And with overburdened SOC analysts, delayed responses, alert overload, and coverage gaps, using AI to your advantage has become a necessity. AI-powered analysts can help you detect patterns your teams might miss, respond to never-ending threats, and sort out incoming data.

This is where Secure.com's Digital Security Teammates flip this model on its head. Instead of having humans handle all operational work, teammates handle the routine grind while humans focus on judgment, complex investigations, and strategic decisions.

But what does that shift actually look like in practice?

Old SOC: How Traditional SOCs Operate

In most security operations today, the workflow follows a familiar pattern:

Alerts arrive constantly

Your SIEM, EDR, and other security tools generate hundreds or thousands of alerts. Each one needs attention, but most lack context; they flag anomalies without explaining whether those anomalies matter.

Analysts triage manually

Someone has to review each alert, gather context across multiple tools, correlate the information, and determine whether it's worth investigating further. For many teams, manual alert handling consumes much of the workday.

Investigations require tool-switching

When an alert does need investigation, analysts open multiple consoles: identity management, VPN logs, and ticketing systems. They're copying information between systems, building context manually, trying to piece together what actually happened.

Response is manual and documented

Taking action, revoking credentials, or blocking an IP, requires logging in to different tools, executing commands, and then documenting what was done and why in ticketing systems.

Coverage has gaps

Most teams can't afford accurate 24/7 coverage. Night shifts are minimal. Weekends are on-call only. The work that happens outside business hours often waits until someone is available, or wakes someone up who then works tired.

Knowledge lives in people's heads

Experienced analysts know which alerts are false positives specific to your environment. They know who to contact in different departments. They understand the context that makes some anomalies normal. When they leave, rebuilding that institutional knowledge takes months.

It makes you wonder what fundamentally separates old SOCs from new SOCs.

SOC Comparison Card

What are the main differences between how old SOCs and new SOCs handle alert triage?

Old SOCs handle alert triage manually with high volumes of alerts across disconnected tools, validating each one, and documenting incidents by hand. Modern SOCs use AI, machine learning, and automation to connect, enrich, and prioritize alerts. In short, modern SOCs move from manual, human-dependent processes to more brilliant, automated workflows that make triage faster, more accurate, and proactive.

Why Traditional SOCs Can't Keep Up

Traditional SOC and SIEM solutions can't help you because of the following reasons:

Context Gathering Card

Why do traditional SOC teams spend so much time gathering context before actual security analysis?

Traditional SOC teams spend so much time gathering context because their tools exist in silos, forcing analysts to pull information from separate systems manually. Each alert needs classification based on asset value, user behavior, threat intelligence, and historical incidents before SOC analysis. This manual process is slow and prone to errors, especially given the high volume of alerts most SOCs face daily.

Old SOC vs New SOC: How Digital Security Teammates Operate

Alert response in traditional SOCs is often emotional panic when analysts see something unfamiliar for the first time, or numbness when they encounter the same false positive for the 200th time.

AI can provide context and the support you need, including sorting SIEM data, allowing IT admins to secure software, and using correlation points that require some level of reasoning.

But the best part is that AI can provide data you can check and validate. AI can provide contextual data, with a human in the loop making decisive calls.

AI can help you route requests to the proper disposition with supporting evidence for any person to review. You have to fight fire with fire, and AI can actually save your time. The fundamental workflow changes when Digital Security Teammates handle operational tasks:

Alerts get triaged automatically

The AI teammate processes incoming alerts using your environment's live knowledge graph, understanding baselines, organizational context, and defined risk parameters. It doesn't just flag anomalies; it determines which anomalies actually matter based on your specific environment.

Analysts review decisions, not raw alerts

Instead of starting from "here's an anomaly, go investigate," analysts start from "here's what this alert is, here's the context we gathered, here's what we assessed, here's what we recommend." The evidence is already collected and correlated.

Investigations start with context, not from scratch

When an alert needs human attention, the relevant information from across your security stack is already assembled. Recent access patterns, device history, user context, similar past events—all presented together, not gathered tool by tool.

Response can happen through conversation

Approving actions can occur in Slack or Teams. The security teammate can execute within defined guardrails, document automatically with a complete rationale, and confirm completion. This often eliminates the need to VPN in or manually update tickets.

Coverage can be continuous

Digital Security Teammates are designed to operate 24/7 with consistent quality. Work that happens at 3 am gets the same triage rigor as work at 3 pm. Humans can maintain reasonable working hours while security operations continue around the clock.

Knowledge accumulates in the system

Decisions include their rationale. Actions are documented with context. When team members change, the operational expertise remains—new analysts can see how similar situations were handled previously and why.

What Actually Changes

In traditional SOCs, Humans perform both operational work (triage, evidence gathering, documentation) and analytical work (investigation, decision-making, strategy). Since operational work is constant and time-consuming, it crowds out everything else.

With Digital Security Teammates: Teammates perform operational work. Humans perform analytical work. The same people spend their time differently.

This creates a leverage shift. An analyst manually triaging can process a limited number of alerts thoroughly each day. An analyst supervising AI teammate decisions can oversee significantly more because they're reviewing analysis rather than doing it from scratch.

The practical implications:

Time allocation shifts dramatically

Organizations deploying Digital Security Teammates report 70% less manual security work. That time shifts toward complex investigations, threat hunting, and program development rather than mechanical triage.

Response speed increases

When evidence-gathering occurs automatically, investigations start from a position of knowledge rather than ignorance. Organizations commonly report 45-55% faster incident response—not because humans work faster, but because they're not spending time gathering information.

Coverage improves without hiring

Continuous AI-powered teammate operations mean alerts can be handled overnight, on weekends, and during holidays—with humans reviewing decisions rather than being on-call to make every decision in real time.

Quality becomes more consistent

Triage quality in traditional SOCs can vary based on analyst experience, time pressure, and fatigue. Security Teammate triage applies defined logic and thoroughness regardless of volume or timing.

Scaling doesn't require linear headcount growth

Adding security capacity in traditional models means hiring more people, with all the time and cost that entails. Adding teammate capabilities means expanding modules, which happens in days rather than months.

The Trust Factor

All of this sounds promising. But there's a question every security team asks when considering AI-backed operations. As a SOC analyst, you must be thinking: How does an AI SOC analyst ensure AI's output is unbiased and accurate? The short answer and the critical difference that make this shift possible are explainability.

Traditional automation executes predefined rules. When it takes action, you know what happened, but not necessarily why, in verifiable terms. Digital Security Teammates document their reasoning for each action, including which signals triggered analysis, which policies were applied, and what the risk assessment showed.

This isn't just about compliance, though audit trails matter. It's about your team actually trusting the system enough to rely on it. Your analysts won't accept recommendations they can't verify. They won't approve actions without understanding the logic behind them. Transparency Traces show the work, which means your team can validate the reasoning, identify where tuning is needed, and build confidence over time.

What This Means For Security Teams

The headcount crisis isn't resolved. The average time to fill security positions remains 247 days. The threat landscape continues to scale. Tool sprawl keeps generating more work, not less.

Digital Security Teammates don't eliminate these challenges, but they change the equation. Security teams can achieve broader coverage and faster response without proportional headcount growth. Analysts can focus on work that requires human expertise instead of grinding through operational tasks.

The shift is from security operations that require impossible human scale to operations where humans have actual leverage. Not by eliminating judgment—judgment matters more than ever—but by eliminating the exhausting work that prevents your team from applying their judgment effectively.

Traditional hiring takes quarters to complete. Teammate deployment can happen in days. Traditional coverage typically requires multiple people per position for shift coverage. Teammates provide continuous operations while humans maintain sustainable schedules. Traditional scaling requires more people. Teammate scaling requires configuration.

AI Triage Card

Can someone explain how AI-powered alert triage changes SOC analysts' daily workflow?

AI-powered alert triage changes SOC analysts' daily workflow by automating much of the repetitive, time-consuming work. Every day, routine tasks such as initial investigation or containment can be automated, allowing analysts to focus on deeper threat analysis and decision-making.

This is what it looks like when security operations finally align with the constraints teams actually face: finite humans, an infinite threat landscape, budget realities, and the need to attract and retain talent in a brutal hiring market.

The difference between old SOC and new SOC isn't about better tools. It's about work distribution that actually makes sense—humans doing what humans do best, teammates doing what can be systematized, and both working together with complete transparency and control.

Organizations report measurable outcomes: a 70% reduction in manual work, incident response that's 45-55% faster, and automatically generated audit-ready evidence. More importantly, their analysts report working on actual security problems rather than the operational grind, and having the capacity for proactive work rather than just keeping up with the queue.

Because ultimately, this isn't about doing less security with fewer people. It's about doing more security with the people you can actually hire and retain. It's about building programs that scale to current threats without requiring impossible headcount. It's about giving your analysts back the job they trained for.

That's the shift. That's what changes when you stop drowning.

FAQs

What are the advantages of using playbooks for incident response in modern SOCs? ▼

Modern SOCs standardize and automate repetitive incident response tasks by relying on tried-and-tested playbooks to speed up response times and free analysts to focus on complex investigations. Additionally, playbooks create an auditable record of actions, improving compliance and enabling continuous optimization of SOC processes.

What metrics should SOCs use to measure the effectiveness of their alert triage process? ▼

SOCs can measure alert triage effectiveness using standard metrics, such as mean time to detect (MTTD) and mean time to respond (MTTR). False-positive and false-negative rates help assess the accuracy of alert prioritization. Alert volume versus actionable incidents shows how well noise is filtered out, while analyst workload and efficiency indicate whether automation is reducing manual effort.

How can SOCs ensure that critical alerts receive immediate attention without overwhelming analysts? ▼

Critical alerts that need immediate attention are identified through automation and AI, which prioritize them by risk and impact while filtering out low-value noise. Automated playbooks can handle routine or lower-priority alerts, freeing analysts to focus on high-risk threats.

What are the most effective ways to document triage decisions in a modern SOC? ▼

The most effective way to document triage decisions in a modern SOC is through integrated platforms that automatically log actions, findings, and conclusions in a structured, centralized system. Using SOAR tools or case management dashboards ensures every alert and response step is recorded, including automated actions taken by playbooks.

How do standardized scoring metrics help SOCs align alert prioritization with organizational risk tolerance? ▼

Standardized scoring metrics for SOCs translate raw alerts into clear, actionable risk levels aligned with the organization's tolerance. These scores are based on factors such as asset criticality, threat severity, and potential business impact. By viewing and analyzing these scores, SOCs can consistently prioritize which alerts require the most attention.

Conclusion

The choice isn't whether to adopt AI; it's whether to drown or adapt. Traditional SOCs can't keep pace with the speed and scale of modern threats. Digital Security Teammates can manage the mechanical grind while analysts focus on critical thinking, delivering 70% less manual work and 45-55% faster response. Your analysts didn't train to babysit SIEM queues; they’re trained to investigate threats and build resilient programs.

Old SOC vs. New SOC: From Drowning in Alerts to Actually Doing Security