The role of generative AI and agentic AI in modern IT and cybersecurity

Ivett Dobay

Generative AI delivers clarity and insight, while agentic AI takes action. Learn how combining both transforms IT operations, accelerates SOC response, reduces risk, and creates measurable business value.

Two AI approaches, different roles, a shared business objective

In corporate discussions about artificial intelligence, AI is often treated as a single, unified technology. In practice, however, we are talking about solutions that fulfill very different roles. Two of the most influential concepts are generative AI and agentic AI—approaches that create business value in distinct yet complementary ways.

Imagine a car. In this analogy, generative AI is like a navigation system: it shows the possible routes, summarizes options, and provides recommendations. It interprets and presents information—but it does not drive the car.

Agentic AI, by contrast, is like a self-driving system: it not only analyzes the situation but also makes decisions and takes action. It brakes, accelerates, avoids obstacles, and continuously adapts to the environment to reach its goal.

This distinction—between interpretation and active execution—fundamentally defines how these two AI approaches can be applied in enterprise IT and cybersecurity.

Monitoring and operations as a key domain of enterprise IT

One of the cornerstones of enterprise IT is operations and monitoring, which ensure system availability, performance, and stability. In modern environments, monitoring is no longer just a technical concern—it is a business-critical function.

Organizations must continuously answer questions such as:

What is happening in our IT systems right now?
Where are the bottlenecks and risks?
How do these issues impact business operations?

Challenges and bottlenecks of traditional approaches

Traditional monitoring and operations models face several persistent challenges:

too many isolated alerts,
complex and time-consuming root cause analysis,
human overload,
slow decision-making.

These issues not only reduce operational efficiency but also pose direct business risks.

Generative AI in IT operations – a tool for transparency

In IT operations, our approach places generative AI in a central role. Here, the primary objective is not autonomous intervention, but fast and accurate situational understanding.

Generative AI–based solutions:

interpret data from monitoring systems, logs, and metrics,
summarize events in both business and technical language,
help operators prioritize issues,
and support well-informed decision-making.

In this role, generative AI functions as the organization’s navigation system: it helps teams navigate complex IT environments, reduces uncertainty, and accelerates operational responses.

Agentic AI in cybersecurity – an active role in the SOC

In cybersecurity—especially within the operation of a Security Operations Center (SOC)—the focus shifts toward active, goal-driven behavior. During a security incident, rapid detection and appropriate response are critical business factors.

In SOC-supporting Analyst solutions, agentic AI therefore plays a key role. This AI:

continuously monitors security events,
uncovers correlations between isolated alerts,
identifies attack patterns and chains,
and prepares decision-making within the incident response process.

Agentic AI does not “decide on behalf of the company” autonomously. Instead, it operates with controlled autonomy: its goal is to reduce the burden on SOC professionals, minimize the likelihood of human error, and enable faster, more consistent responses.

In this context, agentic AI fulfills the role of a self-driving function: it actively participates in processes while human control remains firmly in place.

When analysis and action converge

From a business perspective, real value lies not in using generative or agentic AI in isolation, but in enabling them to work together within a single ecosystem.

Generative AI provides clarity, transparency, and context.
Agentic AI delivers speed, consistency, and goal-oriented execution.

EURO ONE’s solutions bring this collaboration to life in practice—for example, on the operations side, generative AI supports better decision-making, while in the SOC, agentic AI enables fast and effective incident response.

Business benefits from a decision-maker’s perspective

The coordinated use of generative and agentic AI delivers measurable business benefits:

faster decision-making,
reduced operational and security risk,
more efficient use of resources,
more predictable IT and security operations.

For organizations, this is not merely a technological consideration—it is a source of competitive advantage.

Generative AI and agentic AI represent two distinct approaches with different roles but a shared goal. One helps organizations understand what is happening in their systems; the other helps them act quickly and consistently.