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Discover how to harness the power of AI in your SOC without falling into common pitfalls. Learn about effective integration strategies and best practices from industry experts at SANS Security Central 2026.
AI integration in SOC workflows has both benefits and drawbacks. 40% of SOCs use AI or ML tools without intentional operational integration, while 42% rely on them "out of the box". To achieve operational value from AI, refine existing workflows and enable testing and experimentation. AI excels in detection engineering, threat hunting, software development, and analysis. Integration of AI into SOC workflows requires careful planning and execution.
The future of security operations centers (SOCs) is rapidly evolving, and one key aspect that is gaining significant attention is the integration of artificial intelligence (AI). The proliferation of AI in modern SOC workflows has both benefits and drawbacks. While it can provide reliable support for various tasks, its impact becomes more predictable and useful when applied to specific, well-bounded problems with clear expectations for where AI can be used.
A recent survey by SANS revealed that 40 percent of SOCs use AI or machine learning (ML) tools without making them a defined part of operations, while 42 percent rely on these tools "out of the box" with no customization at all. This lack of intentional approach to operational integration has led to a familiar pattern: AI is present inside the SOC but not operationalized.
To achieve consistent operational value from AI, it is crucial to refine existing workflows and enable testing, development, and experimentation for expansion of capabilities. By narrowing the scope of problems and validating logic, teams can treat the output with the same rigor they expect from any engineering effort. The opportunity lies in refining existing categories of work rather than creating new ones.
In various areas of SOC operations, AI can provide reliable support. One key example is detection engineering, where AI tends to be ineffectively applied unless it's targeted at a well-defined problem that supports ongoing operational validation and tuning. A clear case in point is the machine learning exercise from SANS SEC595: Applied Data Science and AI/ML for Cybersecurity course, which uses an autoencoder to assess the reconstruction loss from a machine learning-tuned model. This approach can help identify anomalous streams flagged as threshold-violating.
Another critical area where AI excels is in threat hunting. Hunting should be seen as a research and development capability of the SOC, where analysts explore ideas, test assumptions, and evaluate signals that are not yet strong enough for operationalized detection. While AI can pilot an approach, compare patterns, or check whether a hypothesis is worth investigating, it does not decide what matters.
AI is also highly beneficial in software development and analysis, particularly when reducing mechanical overhead. Analysts write Python to automate investigations, build PowerShell tooling for host interrogation, and craft SIEM queries tailored to their environment. While AI can produce draft code or accelerate logic construction that analysts previously built by hand, the human who understands the system must interpret and validate everything the model generates.
Lastly, automation and orchestration are key areas where AI integration can provide significant benefits. By leveraging AI to generate candidate logic or highlight unusual patterns, analysts can speed up early stages of analysis while still being responsible for interpreting the environment and deciding what a signal means.
The integration of AI into modern SOC workflows requires careful planning and execution. It is crucial to establish clear expectations for where AI can be used, how output is validated, that updates are done on an ongoing basis, and that analysts remain accountable for the protection of information systems.
Related Information:
https://www.ethicalhackingnews.com/articles/The-Future-of-Modern-SOC-Workflows-Mastering-the-Art-of-AI-Integration-ehn.shtml
Published: Tue Dec 30 04:39:49 2025 by llama3.2 3B Q4_K_M
