AI-driven SOCs are seemingly everywhere now, making their timely mark on the cybersecurity industry and promising to revolutionize the sector. If everything said about them is to be believed, they truly can. But before diving wholesale into the first AI SOC you see, it is integral to ask a few questions.
But first, a critical introduction.
What Do AI SOCs Bring to the Table?
“As organizations grapple with an unrelenting surge in security alerts and ever-more sophisticated cyber threats, the security operations center (SOC) is undergoing a fundamental transformation,” notes Prophet Security, a leading AI SOC Platform provider
AI-driven SOCs offer a revolutionary approach to cybersecurity. Instead of using the power of AI to enhance the performance of a few point solutions, AI SOCs automate, orchestrate, and improve the entire detection, investigation and response process across a coordinated string of tools. By integrating AI capabilities across the length of your security stack, AI SOC platforms remove much of the heavy lifting still left on SOCs after the tools have done their jobs.
The end result is tools running on autopilot, coordinated by an intelligent AI SOC solution that can glean data, correlate and corroborate alerts, normalize data, eliminate false positives (all previously the SOC’s responsibility), and provide sterilized, enriched threat intelligence ready to be actioned upon. In many cases, AI SOCs can even mitigate low-level threats without human involvement.
With that in mind, here’s what to know before you invest.
1. Does It Feature Full-Stack Integration?
The answer to this should be yes. To be truly effective, your AI SOC needs to not only ingest alerts from across EDR, SIEM, cloud, and identity tools, but also integrate with contextual data sources that will be useful during the investigation. This lays the foundation for unified triage and investigation, and it’s what your SOC would do if it were there. AI-driven SOC platforms should mimic this, only faster, better, and stronger.
2. Does It Prioritize Security and Data Privacy?
This is another important one and can even amount to a make-or-break. An AI SOC platform should take data security seriously and never take the liberty of training its models on raw customer data. That means ingesting your, and others’, sensitive information to improve its overall algorithms and output.
Additionally, whether it provides a single vs multi-tenant architecture will be critical for customers with strict data segregation requirements.
3. What Level of Autonomy Does It Possess?
This is a huge differentiator among AI SOCs. All AI can “autonomously” take on some tasks, but it is only with the use of agentic AI that autonomous reasoning and dynamic execution truly takes place. Typical AI SOCs will feature generative AI. While good, this alone does not have the ability to do more than answer user prompts with insights from existing data – a useful feature, to be sure.
However, agentic AI goes a step further by making autonomously acting on alerts, deciding which alerts should be marked as benign vs suspicious alerts that need further investigation, and even escalation. In this way, Agentic AI empowers AI SOCs to autonomously analyze, determine, and respond to threats in real time.
4. Is It Improving the SOC Metrics that Matter You?
When you’re investing in AI, you need to feel the benefits in the metrics that your SOC cares about. A good AI SOC platform should reduce key indicators like mean time to contain (MTTC) and mean time to respond (MTTR) by up to 10X. It should also significantly improve or completely eliminate alert dwell time, which is the time it takes from when an alert fires until it’s acted upon by an analyst or AI SOC solution.
The right AI SOC should be able to take on a large portion of Tier 1 and Tier 2 triage and investigation tasks that bog down typical investigations.
5. Is It Environment Agnostic?
Many AI SOC platforms work best – or will only work – within a specified environment. Microsoft Copilot is bound by the Microsoft ecosystem, Charlotte AI is best realized among CrowdStrike customers, and so on. If you are already aligned with one of these vendors, that could be just the answer for you.
But if you are looking to scale and expand beyond a single-vendor stack, do your homework and seek out an AI SOC provider that is environment-agnostic.
6. Are Playbooks Static or Malleable?
Some AI SOC tools are built off static playbook plays. While this certainly brings automation to the table, it neglects one of the key benefits of having AI in the first place – the ability to continuously learn and adapt. Playbook plays should respond based on new information.
As the AI SOC’s adapts to an organization’s unique contextual data, scenarios, and historical actions, it should apply those learnings to future investigations.
7. Is It Data Agnostic?
In an AI SOC platform, being data agnostic means that the AI model can pull in data of all sources and types. This is ideal for addressing companies with complex and diverse data stores, or in situations where data available for training may be limited or unreliable. This means the AI SOC can function regardless of whether the data lives in a SIEM, data lake, or even a cloud storage service like S3, which gives it the ability to “pull in context from anywhere” – a much more flexible approach.
Conclusion
Are AI SOCs the way of the future? They may already be the way of the present.
Gartner predicts that by next year, 75% of SOCs will be using AI analysts. AI SOCs will be the vehicles for these analysts, and those that learn to implement them now will be that much ahead of the game – and attackers, who are already running rampant with malicious AI techniques. The World Economic Forum notes how bad actors already diligently exploit AI models to “refine tactics, probe defenses and coordinate attacks across different geographies.”
The die has been cast: threat actors are leveraging AI’s powerful orchestration capabilities to launch ever-better attacks. Defenders can’t afford to stay behind when protecting against them.
And now, the essential question: Will AI-native SOC platforms “replace” your actual SOC? No. They will only remove the busy work so your SOCs can get right to what matters most. And in light of overwhelming AI threats, that’s no longer hours of manual data cleansing.
Triaging and investigating alerts has long been a manual, time-consuming process that strains SOC teams and increases risk. Prophet Security changes that. By leveraging cutting-edge AI, large language models, and advanced agent-based architectures, Prophet AI SOC Analyst automatically triages and investigates every alert with unmatched speed and accuracy.
Prophet AI eliminates the repetitive, manual tasks that lead to burnout, empowering analysts to focus on critical threats and improving overall security outcomes.
Visit Prophet Security to request a demo today and see how Prophet AI can enhance your security operations.
