SOC For All: Why Every Company Can Now Afford One

For most of its history, the Security Operations Center (SOC) has been a privilege of the few. Building one meant millions in technology spend and round-the-clock analyst coverage. Unsurprisingly, for years, SOCs were a privilege of the few - large enterprises and organizations with high-risk profiles, where budgets and scale justified the investment.

Everyone else was left with partial coverage or had to outsource.

That reality is changing.

AI has flipped the SOC equation. What was once out of reach for all but the largest enterprises is now accessible and affordable for nearly every company that needs one.

The risk every company faces

By now, almost any 9-year-old knows that cyberattacks threaten every company.

It's no longer just banks and financial giants in the crosshairs. Over the past decade, cyberattacks have expanded into every sector, from e-commerce sites to research institutes to local hospitals. Recent data from the 'VikingCloud 2025 SMB Threat Landscape' report shows the trend clearly: one in three SMBs was hit by a successful cyberattack last year.

Attackers don't discriminate by size, industry, or geography.

Even Dior, The North Face, and Pizza Hut Australia suffered massive data breaches in the past few years.

What matters is the impact. A single successful attack can:

• Steal sensitive information, destroying customer trust.
  A 2023 Vercara / Digicert survey found 75% of U.S. consumers said they would stop purchasing from a brand after it suffered a cybersecurity incident.
• Disrupt business continuity, causing days of downtime and lost revenue.
  According to Arcserve's 'State of Data Resilience in the Enterprise' research report, nearly half of U.S. companies report significant revenue loss due to a breach.
• Trigger regulatory fines, draining financial stability.
  According to IBM's 'Cost of a Data Breach 2023' report, 20% of organizations that experienced a data breach paid $250k or more in regulatory fines.

The nerve center for Enterprise Security

The SOC is the most efficient weapon companies have in dealing with an attack.

It's where detection, investigation, and response converge, often determining whether a company survives an incident or suffers catastrophic loss.

SOC adoption grew exponentially as:

• Cyber threats escalated to targeted breaches and large-scale attacks that disrupted businesses.
• Companies needed a dedicated team and hub to detect, investigate, and respond in real-time, not just rely on IT helpdesks.
• The explosion of log data from firewalls, IDS, endpoints, and SIEMs added more complexity, making a centralized operations layer essential.

For many organizations, the SOC was forced into existence by regulations such as:

• Data protection laws, such as GDPR in Europe and CCPA in California, require companies to prove they can detect, respond to, and report breaches quickly.
• Industry mandates such as HIPAA (Healthcare), PCI-DSS (Payments), and SOX (Finance) forced companies to invest in monitoring and incident response to avoid penalties.
• Critical infrastructure rules in sectors like energy and transportation demanded 24/7 monitoring of environments that couldn't afford downtime.

In effect, SOCs became unavoidable. Even companies that didn't see security as a top business priority eventually had to meet compliance, privacy, and industry standards.

For many, outsourcing to an MSSP or MDR became the quickest path to "check the box", but it rarely delivered the depth and standard of the intended protection.

Why SOCs are out of reach

The barriers to building an in-house SOC are overwhelming:

• Staffing costs: For a basic in-house SOC (mid-sized enterprise with 2k employees), around 7 analysts are required to maintain 24/7 coverage.
  At an average U.S. salary of $120K each, labor comes to about $1M annually.
• Technology costs: SOC tooling requires a stack of SIEMs, intrusion detection tools, EDR/XDR platforms, and orchestration layers such as SOAR. Purchasing, integrating, and upgrading these solutions is a never-ending investment.
  
  Basic in-house SOC (mid-sized enterprise):
  

• SIEM licensing and storage: $250–$400K annually (often volume-based).
• Endpoint detection/response (EDR/XDR): $150K–$250K.
• Total technology spend: ~$500K–$700K annually.

The heavier the log ingestion and the larger the digital footprint, the steeper these costs climb. Technology alone often consumes as much as or more than analyst salaries.

• Scaling with growth: A SOC analyst can only process a limited number of daily alerts. As a business expands by adding endpoints, applications, and digital infrastructure across departments, alert volume rises proportionally. Organizations must reinforce shifts with additional analysts to keep pace, driving linear headcount growth simply to maintain coverage. On top of that, the industry-wide talent shortage and high turnover from burnout, as well as scaling an existing SOC, become both costly and oftentimes impossible.
• Operational complexity: Building a SOC is not plug-and-play. It requires several months to plan, integrate tools, define processes and rules, and staff appropriately. Furthermore, everything must be maintained, tuned, and optimized continuously to keep up with the never-ending expansion of the threat landscape.

For many mid-sized and even large enterprises, the costs were prohibitive, and the people were unavailable, making the legacy model unsustainable. Outsourcing wasn't even a conversation for smaller businesses - it was the only path.

To summarize, a medium-sized enterprise building a basic in-house SOC can expect to spend roughly $1.5—$2M annually—about $1M on staffing and $500K—$700K on technology.

The outsourcing workaround

When building wasn't an option, humans did what they do best and outsourced.

Managed Security Service Providers (MSSPs), SOC-as-a-Service vendors, and Managed Detection and Response (MDR) providers filled the gap.

Why outsourced security became a standard

MSSPs and MDRs rose because they solved several pressing challenges:

• Increasing threat complexity: Organizations faced an overwhelming number of sophisticated cyberattacks.
• Lack of in-house resources: Recruiting, training, and retaining cybersecurity talent proved difficult.
• Regulatory compliance: Stricter privacy and security rules require expertise to stay consistently compliant.
• Cost-effectiveness: Outsourcing security monitoring and management appeared cheaper than building an internal SOC.

The limitations of outsourcing

But the model came with trade-offs:

• High recurring fees: MDR or MSSP contracts often cost $250k—$1 M per year, with pricing tied to log/alert volume, endpoint count, or premium services.
  Costs scale quickly as businesses grow.
• Shallow investigations and missed attacks: Without deep familiarity with organizations' environments, MDRs often escalate borderline alerts back to the in-house team.
  This results in missed detections or delayed responses when speed matters most.

• Unclear value: Many security leaders question whether MDRs truly add value or create another layer of tickets. "Are they even doing something for me?" is a common refrain when alerts keep flowing back with little context or ownership.
• Responsible but not accountable: Outsourcers may detect and notify, but if a breach occurs, they bear little consequence. As one CISO put it: "You're handing over the keys to the guard towers to someone who doesn't carry the risk if those fail."
• Loss of context: MDRs often forget details you've already shared, because you're rarely working with the same analyst twice. Rotating teams means no one builds deep familiarity with your environment, and context gets lost.
• Generic coverage: MSSPs balance dozens or hundreds of customers at once. Their analysts don't know your environment intimately, and critical alerts are often passed back to in-house teams for follow-up.

Outsourcing might have solved the staffing barrier, but it created new costs, accountability, and trust challenges, which were unavoidable pills to swallow.

While MSSPs and MDRs face reputational damage if they fail, the breach's legal, financial, and operational consequences almost always remain with the customer.

The AI shift

The technological progression of AI in security operations has redefined what a SOC can realistically achieve. Where legacy automation relied on static rules or rigid SOAR playbooks, today's platforms leverage large language models (LLMs), contextual reasoning, and real-time augmentation to replicate the judgment and actions of human analysts at unprecedented speed.

Precision triage for any scale

Most alerts generated in modern environments are duplicates or false positives. SACR's '2025 AI SOC Landscape Research' found that 40% of alerts are never investigated, and of those that are, 90% prove to be false positives. Traditionally, analysts had no choice but to sift through this flood manually, losing time and visibility on real threats.

AI-driven SOC platforms now ingest and triage thousands of alerts in parallel. Using LLMs, correlation engines, and enrichment pipelines, they can:

• Discard low-confidence noise that would otherwise consume analyst cycles.
• Cluster-related signals are sent into a single incident for faster context building.
• Escalate only high-fidelity threats with reasoning chains and evidence trails that security professionals can verify.

This augmentation transforms security professionals from log reviewers into decision-makers. Instead of battling alert fatigue, they focus on the small fraction of strategic tasks requiring expertise and judgment.

A sustainable virtual SOC architecture

In the legacy model, a 24/7 SOC required three analyst shifts per day, often a 7-person staff, just to maintain coverage. AI adoption is reevaluating that model.

AI-driven SOC platforms now provide what amounts to a virtual Tier-1 analyst layer, capable of performing enrichment, correlation, and initial investigation.

Human experts act as supervisors, validating outputs and guiding escalation paths.

In practice, this allows organizations to:

• Run with a single on-call analyst or small team overseeing the AI system, rather than full 24/7 manual shifts with hands on keyboards.
• Delegate repetitive triage, investigation queries, and enrichment steps to AI triage agents.
• Rely on automation to rapidly contain routine incidents, while reserving human expertise for novel or complex cases.

The result is a cost-efficient, scalable SOC model that provides true 24/7 coverage without the traditional burden of hiring entire shifts of analysts. AI absorbs the growth, allowing teams to expand security operations without ballooning costs or burning out staff.

Operational impact

This transformation slashes staffing requirements, reduces costs, and enables continuous monitoring without the traditional overhead. More importantly, it expands access: Organizations that previously lacked the resources to run an SOC can build one virtually, within weeks, not months.

In short, human scale is no longer a SOC limitation. LLMs and augmentation pipelines have enabled everyone to detect and respond faster around the clock.

The democratization of the SOC

Imagine if only the biggest retailers, like Walmart or Costco, could afford a dedicated 24/7 help desk staffed with people who knew their systems inside and out. Smaller retailers would have to outsource to a shared call center that juggles dozens of companies simultaneously.

The result? Long wait times, repeated questions, scripted responses, and, ultimately, many of the toughest issues are bounced back to the customer.

For years, cybersecurity was exactly like that. Large enterprises could afford fully staffed SOCs embedded in their environments. In contrast, others outsourced to MSSPs and MDRs, where analysts monitored dozens of customers at once and pushed many alerts back for follow-up.

AI has changed that equation.

It has enhanced existing SOCS and made the dream of having one a reality for companies that desperately need it but could never afford it.

• For mid-market enterprises, AI enables the creation of new SOCs where none existed. Even small teams can now achieve enterprise-grade monitoring and response for a fraction of the cost.
• For large enterprises, AI enhances existing SOCs by reducing noise, conserving staff energy, and freeing analysts to focus on high-value strategic work.

And the adoption curve is steep. According to SACR's 2025 AI SOC Market Landscape report:

• 88% of organizations that don't yet run an AI-driven SOC plan to evaluate one in the next 12 months.
• By 2028, security leaders expect AI to handle ~60% of SOC tasks, making AI an operational necessity to handle threats today.

The SOC is no longer reserved for the Fortune 1000. It's now within reach of every company - from regional banks to healthcare providers to SaaS startups.

AI SOC platforms provide 24/7 automated triage and investigation, making security operations affordable, accessible, accountable, and practically the new standard.

About Radiant: The new way of doing SOC

Radiant is pioneering a fresh approach to SOC operations. Its Agentic AI analysts process every alert, suppress false positives, and escalate only real threats with full investigation context and 1-click response for rapid containment. Integrated log management in the customer's cloud removes the scale and cost constraints of traditional SIEMs, making enterprise-grade security operations achievable for any organization.

Watch a short explainer video or book a demo today to learn more about us.

About the Author: Shahar Ben-Hador is the CEO and Co-founder of Radiant Security. He spent nearly a decade at Imperva, where he rose from IT Manager to become the company's first CISO, experiencing the day-to-day challenges of running security operations. Later, as VP of Product Management at Exabeam, he led the building of the products he wished he had as a practitioner.