I began my career in Security Operations Centers, working the analyst desks where alerts never stopped pouring in. Over the years I moved into leadership roles in heavily regulated industries like healthcare, energy, and utilities, and later into consulting on cybersecurity strategy. Throughout those transitions, one constant has remained clear to me: the SOC is one of the toughest but most valuable places to build security strength.
Today, the SOC faces the same foundational challenges it has struggled with for the past two decades. The volume of alerts continues to climb as organizations bring in more detection tools, but the number of people available to triage them has not kept pace. This imbalance has led to analyst burnout, high turnover, and the persistent reality that many alerts go unreviewed. Security leaders have long accepted this risk, focusing only on critical and high-severity alerts, but we know that lower-severity signals can sometimes reveal major incidents.
This is why many CISOs are looking at artificial intelligence as a way to bring order to the chaos. The SOC is not the only place to apply AI, but it is one of the most measurable. Alert queues, metrics, historical baselines, and processes already exist. That structure makes it easier to test whether AI is helping reduce risk, increase accuracy, or improve efficiency.
Using AI in the SOC to Solve Long-Standing Challenges
Simply dropping AI into the SOC is not enough. Security leaders must approach it with strategy in mind. What outcome do you want from the investment? Are you looking to reduce false positives, accelerate investigations, or elevate analyst productivity? Without clarity on these questions, AI can quickly turn into experimentation without results.
There is also the issue of trust. Large language models, for example, are not trained on security operations data. They can generate plausible but incorrect answers that, when scaled across thousands of alerts, introduce more errors rather than fewer. Leaders must take care to use tools designed for the unique demands of security operations.
When applied correctly, AI can transform the SOC team. It does not replace people, but instead shifts their roles toward higher-value work. Instead of grinding through endless triage, analysts can focus on true positives and deeper investigations. Entry-level staff can progress faster, gaining exposure to advanced analysis without years of manual filtering. At the same time, new roles emerge, such as automation engineers who design workflows and human supervisors who provide oversight and business context. AI can provide scale and accuracy, while humans bring judgment, communication, and understanding of the business environment.
I often compare this to other industries adopting AI. A fast-food chain that added AI to take drive-thru orders did not eliminate staff. Instead, it allowed employees to focus on food preparation and customer service, improving both speed and quality. In the SOC, AI delivers similar efficiency. It reduces time wasted on false positives, surfaces the alerts that matter most, and empowers analysts to do the kind of investigative work that truly adds value.
Why AI in the SOC Must Deliver Real Outcomes
At Intezer, we focus on outcomes. We emulate the process a top-tier analyst would follow to investigate an alert, combining forensic-grade automation with context gathering, malware reversing, and identity correlation. Every single alert is investigated, and within two minutes a verdict is delivered. This removes the decades-old acceptance of risk where low-level alerts were ignored. We see customers discovering malicious activity hidden in those ignored alerts, incidents that would have otherwise slipped past.
Speed matters, but accuracy matters more. Without accuracy, automation only multiplies mistakes. By combining both, organizations can reduce burnout, expand coverage, and raise the overall effectiveness of their SOC.
The reality is that this is not theoretical anymore. Large global enterprises, including NVIDIA, Equifax, and MGM, are already proving that AI-driven SOC automation can scale to meet their needs and deliver measurable results.
CISOs and boards want assurance that AI in the SOC is more than just a promise. They want to know if the outcomes are real. The answer is yes. With the right strategy and the right tools, AI can finally resolve the SOC’s long-standing challenges and turn it into a place where people and technology work together at scale.
