Why AI SOC is a Lean Security Team’s Lifeline


Why AI SOC is a Lean Security Team’s Lifeline

How AI is helping mid-sized organizations boost cybersecurity and cut costs

– Subo Guha, Senior Vice President, Product Management, Stellar Cyber

San Jose, Calif. – Jan. 28, 2025

The concept of the Artificial Intelligence Security Operations Center, also known as the AI SOC, is getting a lot of buzz lately. With it comes the potential to deliver better cybersecurity outcomes for organizations of all sizes. Historically, the SOC has been the domain of the large enterprise. Traditional SOCs were built for larger, well-funded organizations with the resources to benefit from a real-time SecOps command center that can monitor, alert, and act upon suspicious or outright malicious activity across the network. Mid-sized organizations with lean security teams and smaller budgets were priced out. 

However, the emerging AI SOC model represents a real opportunity to help level the playing field. By adding AI, automation, scalability, and filling in security gaps for mid-market organizations, AI SOCs can break economic barriers that have prevented smaller organizations from leveraging the same benefits as their enterprise counterparts. 

What is an AI SOC?

When you strip away the hype, an AI Security Operations Center (SOC) is a specialized AI SecOps center consisting of human security analysts and critical layers of AI that work together seamlessly. Using AI and Machine Learning (ML) to do the heavy lifting and fill in the gaps, and the human security analysts to handle more complex analysis and decision-making, the AI SOC enhances the monitoring, detection, and response to security threats. Working together, humans and machines secure their environment more efficiently without sacrificing personnel, costs, or weakening the overall security posture. 

Better, Faster, Stronger

The AI SOC model empowers lean security teams in several ways. First, artificial intelligence automates tasks that once required larger budgets, personnel, and extensive resources. Additionally, an Autonomous SOC model can help lean teams improve their decision-making processes with feedback loops and automated reporting, helping midmarket organizations protect their investments and make better-informed decisions. 

Migrating to an AI SOC model enables lean security teams to:

  • Detect real threats faster. Accelerate the detection of threats, anomalies, and vulnerabilities, ensuring decisive responses and strengthening the security posture of organizations adopting this approach. 
  • Reduce alert fatigue. Siloed tools and disparate data send information without context to SecOps teams, overwhelming human operators manually scrubbing alerts. This leads to burnout, which increases staff turnover, weakening the protection of SOC environments. In an AI SOC, analysts have the benefit of visibility across all systems, historical data, and better context into alerts, so they know what they’re seeing and whether it’s a real threat.
  • Reduce operational costs. Midmarket companies can gain the capabilities of an enterprise SOC at a fraction of the cost while increasing ROI for both technology and staff investment thanks to higher productivity. 
  • Train human security analysts. Stronger learning loops generated by AI automation to improve learning and sharpen skill sets for human SecOps teams. 
  • Build a better bot. Using the in-house knowledge of your security team, you can create a continuous learning system that adapts and learns from new or historical events and actions taken by your SOC analysts. 

It’s important to note that while the AI in an AI SOC can handle routine tasks and process massive amounts of data faster than humans, it lacks the contextual awareness, intuition, and strategic thinking that security professionals bring to the table. This is why human security analysts will always be crucial to the SOC, no matter how advanced AI becomes.

Human-Machine System of the Future

The most effective AI SOCs of the future will be those where humans and autonomous systems work together. Expect to see AI and ML as the heavy lifters, handling more data-intensive tasks and surfacing actionable intelligence that helps the human analysts make faster, more informed decisions. We’ll also see hyperautomation rise and become even more relevant in use cases like automated triage. Multiple AI agents and GenAI-powered response playbooks will help human analysts resolve complex and voluminous security alerts and improve case management workflows. Systems will become more interactive between analysts and AI agents, facilitating continuous validation and decision-making between the two. Human security analysts will serve as more strategic drivers in the AI SOC, making more complex decisions. 

– Subo Guha, Senior Vice President, Product Management, Stellar Cyber


About Stellar Cyber

Stellar Cyber’s Open XDR Platform delivers comprehensive, unified security without complexity, empowering lean security teams of any skill level to secure their environments successfully. With Stellar Cyber, organizations reduce risk with early and precise identification and remediation of threats while slashing costs, retaining investments in existing tools, and improving analyst productivity, delivering an 8X improvement in MTTD and a 20X improvement in MTTR. The company is based in Silicon Valley. For more information, visit https://stellarcyber.ai.



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