SOC & AI: How SIEM tools use artificial intelligence to protect businesses

Introduction

Imagine driving a race car at high speed on an unfamiliar track, without a dashboard, without a co-pilot, and without knowing when the next turn is coming. That's how many companies operate their digital security today: without visibility, without anticipation, without strategy.

And the risks are not hypothetical. According to an IBM Security report , the average cost of a data breach in 2023 was US$4.45 million, the highest value ever recorded in the historical series. This data reflects a scenario in which attacks are becoming more frequent, sophisticated, and silent. Reacting is no longer enough: it is necessary to predict.

It is in this context that the modern SOC evolves. Combining SIEM technology, artificial intelligence (AI), and cybersecurity specialists, it transforms into the co-pilot of the digital operation, guiding decisions, anticipating threats, and adjusting routes with precision.

In this article, you will understand why an effective SOC depends on three pillars : people, tools, and well-trained AI. And how Skyone , with Microsoft Sentinel and the CDC, is creating a new generation of SOCs that are faster, more automated, and smarter.

Shall we go?

What is a SOC and why is it important in cybersecurity?

In an increasingly data-driven world, thinking about cybersecurity without a SOC is like trying to compete in Formula 1 without a team in the pits. There may be movement, but there's no strategy, context reading, or real-time reaction capability.

The Security Operations Center (SOC) is precisely that strategic support: the core that monitors, interprets, and responds to digital security events. But it's not just about "monitoring alerts"; the true role of a SOC is to anticipate failures, identify vulnerabilities, and make quick decisions based on reliable data.

And here's an essential point for those in the middle of the decision-making process: a SOC is not just software. Nor is it just a team of specialists. It's the intelligent combination of people, processes, and technology, evolving today with the support of artificial intelligence (AI).

Let's understand better what this means in practice.

Definition and functions of a Security Operations Center (SOC)

A SOC is an operational center specialized in information security. It is responsible for monitoring , analyzing, and acting upon any suspicious activity that occurs within an organization's systems and networks.

It functions as a tactical command center, where every event recorded in logs, sensors, and endpoints is analyzed for patterns, vulnerabilities, or signs of an attack. Its main functions include:

• Continuous monitoring of systems and networks, 24/7; 
• Event analysis and data correlation to detect threats; 
• Incident response, with clear protocols and rapid action; 
• Investigation and documentation of incidents; 
• Support for regulatory compliance, such as LGPD (General Data Protection Law), ISO, etc. 

But all of this is only possible when there is a solid foundation of qualified people, well-defined processes, and tools that provide the necessary visibility to act quickly. Without visibility , there is no efficient reaction. And without data correlation , there is no informed decision.

This is where technology comes in, as a support, not as an end in itself.

The challenges faced by SOC teams

The complexity of the current scenario imposes daily pressures on SOC teams. Among the most critical are: 

• Alert overload : many SOCs receive thousands of events per day, and most are false positives, meaning alerts that appear to indicate a threat but in practice do not represent a real risk. The excessive volume ends up consuming the team's time and focus;

• Talent shortage : finding and retaining qualified cybersecurity professionals is a global challenge;

• Hybrid and decentralized environments : with cloud computing, mobile devices, and multiple integrations, the security perimeter has become blurred;
  
• Too many disconnected tools : when systems don't "talk" to each other, response time increases and trust decreases;
  
• Many people are mistaken : technology filters the data, but humans are the ones who interpret it. Without the expert's intelligence, all that's received is raw data. AI acts as a reinforcement, expanding the capabilities of analysts without replacing them. In other words, what really works is the combination: person + tool + intelligence.

This reasoning brings to light an uncomfortable, yet essential truth: a SOC that only reacts is always lagging behind . The new paradigm is a SOC that anticipates, that operates with predictive vision, and that feeds on data not only to respond, but to make strategic decisions.

With this structured conceptual foundation, it's time to move on to the next component of this mechanism : the SIEM, which acts as the onboard computer for SOC security, translating raw data into critical signals for decision-making.

SIEM: the on-board computer for safety 

Every high-performance car depends on a system that collects vital information during the race: temperature, fuel consumption, acceleration, malfunctions, engine behavior. In digital security, this system has a name: SIEM.

SIEM ( Security Information and Event Management ) is the tool that allows the SOC to see the whole picture in real time . It records, interprets, and correlates events generated by the entire company's infrastructure.

Without this "on-board computer," the SOC loses context. And without context, there is no efficient decision-making .

What is SIEM and how does it work?

Essentially, SIEM is a system for collecting, analyzing, and organizing security data . It integrates logs and events from various sources (such as servers, firewalls , endpoints , and applications) to identify deviations from the norm and signal risks.

Its operation can be divided into three complementary areas :

1. Structured collection : raw data coming from multiple systems;
2. Intelligent correlation : cross-referencing information to identify suspicious patterns;
3. Generating alerts and reports : sending relevant signals to the security team.

This structure allows the SOC to operate more efficiently , prioritizing what truly matters and reducing the volume of false positives that consume analysts' time and energy.

It's the kind of tool that transforms a fragmented scenario into a continuous and strategic line of sight.

log and event analysis

In today's hybrid, multi-cloud, and remote access environment, centralizing security information is not just a best practice, but a necessity.

Therefore, SIEM acts as an hub , bringing clear benefits to security teams:

• Unifying the risk landscape : a consolidated view of all assets and their behaviors;
  
• Agility in incident response : with automated correlations, the time between detection and reaction decreases;
  
• Reducing operational noise : fewer irrelevant alerts and more focus on what represents a real threat;
  
• Ease of compliance and audits : organized, traceable, and exportable data for regulatory reports.

This level of organization is what allows the SOC to stop reacting and start understanding what is happening — in real time and with context.

But just as important as understanding the present is anticipating what lies ahead . And for that, you need more than just correlating events: you need intelligence. Keep reading to find out!

The AI ​​revolution in SOCs: how SIEM tools are evolving

In an analogy, we could say that security systems based solely on fixed rules function like a race car that only responds to what has already happened: it brakes after the turn, not before .

With the advancement of threats and the volume of monitored data, the simple correlation of events is no longer sufficient. Thus, artificial intelligence (AI) enters the scene as the element capable of transforming the SOC into a truly predictive structure .

The goal is not to replace the human figure, but rather to provide speed and analytical depth , complementing the expertise of professionals. Here, the role of AI is to optimize triage, find subtle patterns, and reduce response time, without taking away the team's decision-making power.

As we have seen so far, technology helps, but it is the combination (people + tools + intelligence) that generates real results . AI, within the SOC, must be trained, contextualized, and integrated into the operation, and not just "connected" as a generic solution.

Next, we will see how this works in practice.

How artificial intelligence improves threat detection

AI applied to SIEM operates continuously, observing the environment, learning from history, and signaling deviations in real time.

Unlike systems that only react to known signatures, AI-based models are able to identify anomalous and undocumented behaviors that escape traditional patterns—something essential in the face of increasing sophisticated and personalized attacks.

• Less time to discover a threat; 
• More precision in what should be investigated; 
• Noise reduction and improved focus.

And most importantly: a faster response , before the incident spreads.

Machine learning for identifying malicious patterns

One of the strengths of AI in the context of a SOC lies in the use of machine learning , which involves training models capable of evolving based on collected data. They are trained from a massive volume of events and, over time, learn what is normal and what represents a real risk in that specific environment.

This learning, however, does not happen on its own. AI only accelerates what it is taught. This means that if the input data is misinterpreted, biased, or out of context, the system learns incorrectly and begins to make decisions based on incorrect assumptions.

Therefore, relying on generic solutions or connecting a "standard" AI to a sensitive environment like a SOC can be as risky as it is useful. Without guidance, governance, and validation , what was meant to protect can become a blind spot .

AI in prioritization and automated incident response

In addition to detecting threats more accurately, AI plays a vital role in prioritizing alerts and automating responses , especially in high-volume event environments.

It analyzes the context of each incident, understands the degree of risk, and suggests (or executes) corrective actions, such as:

• Isolation of suspected machines; 
• Temporary access blockage; 
• ticket generation for investigations;
• Activation of containment protocols. 

Here at Skyone , this automation is orchestrated from an ecosystem that involves the CDC ( Cyber ​​Defense Center ) and tools like Microsoft Sentinel, allowing teams to act with agility , but without losing control of the operation.

More than just a promise, the application of AI in security environments is already a concrete reality in companies seeking to operate with predictability, scale, and speed.

In the next section, we will discuss some practical examples of use that illustrate AI in action within a modern SOC, combining technology, intelligence, and coordinated response.

Use cases: AI in action within a modern SOC

Now that we understand how AI can be applied to the SOC context, it's time to see how this translates into real-world action .

More than just a concept, we're talking about situations that happen daily in companies that need to deal with a dynamic, decentralized, and often unpredictable environment . Here, every second counts, and responsiveness can make the difference between neutralizing a threat or dealing with the consequences of an incident.

Below, we share three real-world situations faced by companies with modern SOC structures, where AI was crucial in intelligently detecting, prioritizing, or responding to risks. These represent what Skyone sees in the field every day, based on projects that combine technology, processes, and people.

Detection of sophisticated and unknown attacks

In a traditional environment , most security systems operate based on known signatures: they compare what happens in the system with previously recorded patterns of attacks.

But what happens when malicious behavior has no signature ? When the attacker simulates legitimate actions and acts slowly and stealthily , hoping not to be noticed?

Imagine, for example, a scenario where a sequence of logins occurs at unusual times , from devices that mimic the patterns of the internal team. At first glance, nothing seems out of the ordinary.

It is in this type of situation that AI excels. Trained to detect subtle deviations in behavior based on the real history of the environment , it can flag risks that escape human eyes and predefined rules. With this, the SOC gains time to act and block the lateral spread of the threat before it consolidates into a full-blown attack.

In such situations, no pre-configured rule would have captured the incident in time . Only the contextual analysis of AI, combined with the team's rapid response, is capable of containing a threat invisible to traditional systems.

Reducing false positives and optimizing human work

In another common scenario, imagine a medium-sized company dealing with over 3,000 alerts per day , most of which pose no real risk.

Even a well-trained security team ends up spending hours analyzing repetitive notifications : routine internal scans, authorized accesses that generate alerts, temporary failures without impact. This consumes focus, energy, and delays important decisions.

By integrating AI into the SIEM, it's possible to teach the system to recognize legitimate behavior in that specific environment. The technology begins to "understand" the context—and, as a result, stops flagging alerts that don't require human action.

The result? reduction in false positives, recovery of team productivity, and focus on what really matters. In other words, AI frees analysts from repetitive tasks, allowing them to concentrate on strategic decisions.

Skyone: How the CDC and Sentinel work together to protect businesses

At Skyone , these illustrative situations reflect what we see every day. The difference lies in how we integrate technology, team, and process.

Our CDC functions as the tactical center of security operations. It's where we transform technology into action , with a team of specialists, validated processes, and a solid foundation of automation.

Using Microsoft Sentinel, we collect, correlate, and classify events with AI support. It acts as the operation's "onboard computer," while we maintain a human perspective on what truly matters. This combination allows us to:

• Responding to incidents with agility and thoroughness, without losing control;
• Generate automated reports and predictive insights for faster decision-making;
• Prioritize alerts based on their actual impact on the business, not just their volume;
• teaching AI so that it evolves with our context.

More than just monitoring, we orchestrate end-to-end security with intelligence, precision, and autonomy. This is because we believe that protecting a business today requires more than just tools : it demands vision, coordination, and the courage to anticipate what hasn't even appeared in the rearview mirror yet.

How about we now find out what these concrete benefits are for SOC teams? Check it out!

Benefits of AI for SOC teams

Talking about artificial intelligence in the SOC might sound, at first glance, like a purely technological issue. But, in practice, the greatest gains are not in the algorithms themselves , but in what this intelligence unleashes within security teams.

When applied purposefully and with supervision , AI removes noise, reduces operational load, and broadens the strategic focus of teams. It transforms the routine of analysts , who stop reacting to each alert and start acting based on context and priority.

In the following sections, we show how these benefits manifest in day-to-day operations, with greater agility, precision, and applied intelligence.

Process automation and increased efficiency

Automation is one of the first areas where AI is making a real impact. By taking over repetitive tasks, it frees up analysts to work where human intelligence makes the most difference . With the support of AI, it is possible to:

• Reduce response time to critical events; 
• Avoid overloading teams by channeling energy towards what is strategic; 
• Maintain continuous surveillance, with real-time risk screening; 
• Identify hidden patterns through automated data correlation. 

By automating intelligently , we strengthen the role of specialists, who then operate with a broader perspective and greater decision-making power.

How Microsoft Sentinel helps our customers at Skyone

To achieve this level of efficiency and orchestration, at Skyone , we use Microsoft Sentinel as a central part of our SOC architecture . It's the engine that allows us to build faster and more contextual operations , offering:

• Continuous collection of data from multiple sources; 
• Behavioral analysis with AI and machine learning ;
• Alerts prioritized according to actual criticality; 
• Orchestration of responses based on dynamic rules and patterns; 
• Dashboards and reports tailored to the specific needs and maturity of each client. 

Integrated with our CDC, Sentinel helps us deliver security with consistency and adaptability , regardless of the size or sector of the business. Through it, we have established a virtuous cycle : AI learns continuously, analysts make informed decisions, and protection improves.

Want to see how AI, Sentinel, and experts can work together in your scenario? Talk to a Skyone expert! We're ready to listen, understand, and build the right solution for your needs right now.

Conclusion

Cybersecurity is no longer just a protective barrier. Today, it's part of the business strategy; a cog that , and continuous adaptability .

Throughout this article, we've seen how the combination of qualified people, well-integrated tools, and applied artificial intelligence is shaping a new generation of SOCs. It's not about abandoning what works, but about accelerating decisions, reducing noise, and increasing responsiveness to ever-evolving threats.

We've also shown how AI , when trained responsibly and aligned with a specialized team, doesn't replace, but expands the reach of human intelligence . And how tools like Microsoft Sentinel, integrated with Skyone , allow us to create security structures that learn over time and act with precision .

Like a well-coordinated racing team, the best results don't come from speed alone. Remember: they come from the combination of track reading, preparation, and orchestrated response .

The journey to intelligent security is just beginning! And if you want to keep up with the trends, practices, and technologies shaping this future, you've come to the right place. Visit the Skyone blog

FAQ: Frequently asked questions about SOC and artificial intelligence

Information security is an increasingly critical issue for companies of all sizes. With the growth of digital threats, questions arise about the roles of SOCs, SIEM technologies, and artificial intelligence in this scenario.

Below, we have compiled direct answers to some of the most common questions on the subject.

What is SOC in IT and what is its role in information security?

A SOC ( Security Operations Center ) is a structure comprised of professionals, processes, and technologies that work in an integrated way to protect an organization's digital environment. Its role is to monitor, detect, and respond to threats in real time, ensuring continuous visibility, rapid response, and strategic control over risks.

What is the difference between SIEM and SOC?

SIEM ( Security Information and Event Management ) is the technology that collects and analyzes security data from various systems, identifying suspicious behavior. SOC ( Security Operations Center ), on the other hand, is the human and operational structure that interprets this data and makes decisions based on it.

While SIEM provides the signals, SOC decides how to act, in a coordinated and business-oriented manner.

Could artificial intelligence replace cybersecurity analysts?

No. Artificial intelligence (AI) is a support tool that enhances analytical capabilities, accelerates alert triage, and helps identify complex patterns. But it doesn't make decisions on its own. The role of analysts remains essential for interpreting context, validating risks, and defining the best responses. The strength lies in the integration between people, processes, and technology.

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Caco Alcoba

With extensive experience in cybersecurity, Caco Alcoba is a true guardian of the digital world. In "Caco's Column" on Skyone's LinkedIn page, he shares sharp analyses on cyber threats, data protection, and strategies for maintaining security in the ever-evolving digital environment. Connect with Caco on LinkedIn: https://www.linkedin.com/in/caco-alcoba/