How SOAR and AI Are Reshaping Cybersecurity in Real Time
For many organizations, SOAR helps reduce false positives, improve consistency, and accelerate response to a growing volume of security alerts. But as threats evolve, so must the tools, and traditional SOAR platforms are reaching their limits.
Cybersecurity teams are under pressure to respond faster, smarter, and with fewer resources. The rise in sophisticated threats has pushed traditional tools to their limits. To keep up, many security operations centers (SOCs) rely on security orchestration, automation, and response (SOAR) to streamline incident response and reduce manual workloads. But SOAR isn’t evolving fast enough on its own. That’s where artificial intelligence (AI) is stepping in — powering better threat detection, smarter decisions, dynamic automation, and a new era of cyber defense.
How SOAR Works
SOAR comprises a category of platforms designed to help security teams manage and respond to threats more efficiently. A SOAR solution connects various security tools, automates repetitive tasks, and enables streamlined workflows for detecting, investigating, and remediating incidents.
At its core, SOAR technology brings together three key functions:
- Orchestration: Linking disparate tools and systems into coordinated workflows.
- Automation: Handling routine response actions without human intervention, such as gathering threat intelligence or escalating alerts.
- Response: Guiding or executing actions to contain, mitigate, or resolve security incidents.
For many organizations, SOAR helps reduce false positives, improve consistency, and accelerate response to a growing volume of security alerts. But as threats evolve, so must the tools, and traditional SOAR platforms are reaching their limits.
The Limitations of Traditional Playbooks
SOAR playbooks were built to handle predictable problems with structured, step-by-step response processes. They work well for common use cases — like phishing remediation or endpoint containment — but they fall short when incidents deviate from expectations.
Why? Because playbooks are rigid. They require predefined triggers, conditions, and actions. If an alert doesn’t match the exact scenario they’re designed for, the automation stalls or (worse) misfires. This is where the limits of traditional SOAR become painfully obvious. Modern threats don’t always follow a script. Attackers use new techniques, blend signals, and move faster than teams can update workflows. In these cases, playbooks alone aren’t enough.
AI can fill that gap. Instead of relying on static logic, AI analyzes patterns across security data, adapts to new inputs, and guides decisions in real time. It brings flexibility to automation, making decisions that evolve with the threat landscape instead of being hard-coded into a single use case.
This shift from rule-based response to intelligence-driven action is where real security gains happen — especially when playbooks reach their limits.
The Rise of AI in Cybersecurity
The volume, speed, and complexity of today’s cyber threats have outpaced what even the most experienced security professionals can handle manually. This is where AI and machine learning (ML) are making a transformative impact. By analyzing vast amounts of data in real time, AI can detect potential threats, prioritize security alerts, and even predict attacker behavior based on patterns in historical data.
Unlike traditional tools that follow rigid rules, AI adapts, learning from new security information, minimizing false positives, and supporting faster, more accurate incident response. It also frees human analysts from tedious triage and enrichment tasks, allowing them to focus on higher-value decision-making.
As organizations aim to improve operational efficiency without increasing headcount, AI has quickly become an essential layer in the modern cybersecurity stack — not just augmenting human teams, but helping them scale.
How SOAR and AI Can Work Together
SOAR platforms were designed to simplify and accelerate response times by automating structured, repeatable tasks, but they were never meant to think. AI brings intelligence to SOAR automation — identifying patterns, prioritizing threats, and enriching data before a playbook ever runs.
For example, AI can detect unusual activity across multiple systems, correlate it with threat intelligence feeds, and determine the severity of the threat in real time. Instead of triggering a fixed playbook on every alert, SOAR can rely on AI agents to decide when action is needed and what level of response is appropriate. That reduces noise, improves decision-making, and helps security teams focus on what really matters.
This synergy is especially valuable in environments flooded with security alerts. AI handles the scale — analyzing vast amounts of data from various security tools — while SOAR provides the structured execution layer. Together, they move teams from manual response to proactive defense.
Combining SOAR with AI unlocks a new level of speed, precision, and scale in cybersecurity operations. Together, they help cybersecurity teams manage growing threat volumes without burning out analysts or missing critical signals.
The key benefits of this integration include:
- Faster incident response: AI accelerates detection, triage, and decision-making; SOAR executes workflows immediately.
- Reduced analyst fatigue: Automating repetitive tasks like enrichment and alert correlation frees up time for deeper investigation.
- Smarter alert prioritization: AI helps distinguish between noise and true threats, minimizing time spent on false positives.
- Context-aware actions: AI brings context from threat intelligence feeds, asset data, and historical patterns, so SOAR playbooks act with precision.
- Scalable security operations: AI-enabled SOAR allows smaller teams to handle enterprise-scale workloads with consistency and confidence.
When deployed together, SOAR and AI don’t just streamline response — they transform how organizations detect, decide, and defend at speed.
Challenges and Considerations
While the integration of AI and security automation offers powerful advantages, it’s not without challenges. Automation is only as effective as the data it draws from, and poor or incomplete security data can lead to misfires and unintended cybersecurity risks.
There’s also a risk in over-automating. Not every alert deserves an automated response, and without human intervention, critical context can be lost. AI must be transparent and explainable so that human analysts can trust its recommendations and override them when needed.
Finally, implementation matters. Stitching together AI tools, various security platforms, and legacy infrastructure isn’t always seamless. Success depends on smart integration, clear policies, and a focus on measurable outcomes.
AI-Powered Security Automation, the Anomali Way
Anomali takes a different approach to automation — embedding multiple layers of AI natively across its Security and IT Operations platform to drive faster, smarter, and more autonomous security outcomes without relying on traditional SOAR solutions.
These capabilities include:
- Generative AI for context-aware response and executive-level summarization of telemetry and threat data
- Agentic AI for automated triage and adaptive threat response
- Natural language processing (NLP) to provide security analysts with conversational interfaces and plain-language investigation
- Real-time threat scoring to prioritize alerts, reduce noise, and accelerate decision-making
- Correlation AI to normalize and deduplicate massive volumes of threat intelligence across feeds and models
- Augmented AI to verify and cross-reference intelligence, minimizing hallucinations and increasing confidence
With features like Anomali Copilot and Macula, these AI layers work together to reduce alert fatigue, eliminate repetitive tasks, and surface the most relevant threats with rich context. Analysts can act faster and with greater clarity, without the need for bolt-on orchestration tools or rigid playbooks.
This is automation that learns, adapts, and scales with the needs of modern security teams — precision, context, and speed in one unified platform.
Smarter Security Starts With AI and Automation
Cybersecurity teams can’t scale with manual effort alone. And while SOAR platforms help streamline known processes, they struggle when threats fall outside the playbook. That’s where AI makes the difference — learning from patterns, adapting to new data, and automating actions that once took hours.
Anomali delivers this intelligence natively, without SOAR. With AI-driven workflows, contextual enrichment, and guided investigation, your team can act faster, smarter, and with greater confidence.
Ready to see how Anomali's security solutions turn threat intelligence into real-time response to enhance your security posture? Schedule a demo.
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