I am sure it is difficult to be SOC analyst.
Every day, they are expected to solve high data problems with half data and twice as much pressure. Analysts are overloaded – not only threats, but also in systems and processes that are designed to help them respond. The instrument is fragmented. Working processes are difficult. The context lives in five places, and alerts never slow down. What has started as a rapid role with high impact, for many analysts, has become a repetitive alert cycle and overload data that offer little opportunity for strategy and growth.
Most SoC teams are also leaning. Last year, Our annual Soc SoC survey It turned out that most SoC consists of only 2-10 full -time analysts. Much has changed after the poll began to track in 2017. Meanwhile, the coverage sphere has exploded, ranging from the infrastructure that was conducted to the previous infrastructure to cloud conditions, the remote end points, SAAS platforms. On scale, this has led to a systemic burnout in the SOC -legitimate business that hinders the possibility of your organization to defend yourself.
The solution to the problem is not a matter of simple increase in number. The longer we treat the burning as a problem with people, the longer we ignore what really goes wrong in SoC. The problem that requires a shift is how the SoC work is developed and performed, as well as how analysts are placed for success.
Enter artificial intelligence (AI). The AI implementation offers a practical way forward, optimizing parts of work that push analysts to the door: repeating steps, cognitive overhead and lack of visible progress. From streamlining ineffective workflows and supporting skills development to facilitate more efficient supervision of the entire team, AI can open wider ways to make the SoC more sustainable work.
Reduced alert fatigue and recurrent load with reasonable automation
Constant low-context alert flow from the fastest ways to drain the SoC command. During the Sans SoC poll, 38% of organizations reported the use of all available data in their Siem. Although it can expand the visibility, it also floods low priority analysts. And without a strong correlation logic or interplatform integration, the collection of a complete picture is still on the analyst. They leave the pursuit indicators in dissenters, combining the context by hand and decide whether the escalation is needed. This is ineffective, depleting and impossible.
SOC teams have been automating tasks for years, but most of this automation relied on delicate logic, such as solid books and static flows that are destroyed as soon as the scenario deviates from the expected. AI changes that. AI automation can remove this pressure by acting as a uniquely powerful context aggregate and an investigation assistant. In pairs with such capabilities as those included in the new model context (MCP), language models can integrate telemetry, the intelligence of threats, assets metadata and the history of the users into one species, adapting to each unique situation that the analyst faces. This gives analysts enriched, specific for resume cases instead of unprocessed events. Clarity replaces assumptions. The answer solutions occur faster and with greater confidence – two things that directly reduce burnout.
The main thing is that, unlike SOAR, AI allows adaptive automation and even makes it easy to be available through the LLM interface. With AI and new standards agents, such as MCP and Agent2agent Protocol, now the future here where analysts can describe what should happen in a simple language, and the system can dynamically create automation by solving what tasks you need to perform and the best way to complete them. Whether it is obtaining data, signal correlation or response coordination, AI can adjusted in real time depending on the context. This flexibility matters, especially if the investigation ways are not always clear and linear.
Construction of Trust Analytics through reasonable feedback
The burnout occurs not only from long hours. Sometimes it stems from stagnation – causes the same job, does not grow or receive significant feedback. If the analyst does not see progress, frustration quickly gets accustomed. This is an area where AI can offer valid support. This allows the analysts to clarify their own work on the go – setting up the logic of detection, troubleshooting of false positives and creating the best requests with quick, focused offers. Real -time feedback, similar to this, is especially valuable for new analysts, but even experienced team members enjoy the opportunity to pressure their approach without waiting for an expert assessment.
These interactions support what the researchers call intentional practice: a purposeful repetition paired with an immediate, effective feedback. This is his weight in gold when it comes to content. According to Sans SoC, “considerable work” and “career progression” were recognized by two best factors for analysts – they received compensation. The teams that have grown up into the daily work process are most likely to be kept people. AI cannot replace human mentoring, but it can help repeat some of its most significant effects on scale.
Helping the SOC leaders manage and strengthen their teams
SOC leaders have a direct effect on burning. However, the lack of time and visibility are often their biggest obstacle to the positive effect. Efficiency data, such as the case load, the quality of the note, the depth of the investigation and the response time, scattered over platforms and research. Without the opportunity to synthesize it, the executives leave to guess who is fighting and why.
AI makes this analysis possible. With access management and workflow data, models can turn the trends of efficiency: what analysts consistently process certain types of threats where the cluster errors or when the quality begins to fall. This understanding allows the executives to train more effectively and assign work based on opportunities, not just accessibility. It also gives them the opportunity to intervene early. The burnout does not proclaim itself. It is built slowly, often out of sight. But with the right overload signals, which contains spaces in the skills, noticing the departure as a quality-leader can take action before the problems become outputs.
Over time, such purposeful support redorates the team. The performance improves, the content is stabilized, and analysts are likely to remain and grow in the role where they feel visible, maintained and adjusted to succeed.
Let’s continue the conversation at Sans Network Security 2025
SoC Burnout is rare immediately. It is built through a repeat without learning, pressure without progress and effort without impact. AI does not remove every stress in SoC, but it can help ease the friction where it is most important.
When this topic resonates, join me at the Sans Network Security 2025 in Las Vegas. I will conduct sessions on the construction of healthy, more efficient SOC-including how to apply II to reduce burnout, streamline work processes and maintain analysts in real conditions.
Sign up for Sans Network Security 2025 (September 22-27, 2025).
Note: This article was written by John Habbard, Senior Sans instructor. Learn more about his story and courses here.
Note: This article was written and introduced by John Habbard, Sen. Sans Institute.
