What You’ll Learn
- Why detection has become a commodity and why the real advantage now lies in investigation and response.
- How Agentic AI works — from reasoning, hypothesis testing, and orchestration to autonomous remediation.
- The evolution beyond SOAR — where static playbooks end and adaptive intelligence begins.
- How human-AI teaming works in practice, allowing AI agents to handle Tier-1 triage while analysts focus on complex cases.
- The governance frameworks (like the Model-Control-Policy model) that make autonomy safe and auditable.
- Real-world examples showing how organizations cut dwell time, reduce analyst fatigue, and double investigative speed.
Inside the Paper
- Comparative analysis: Detection vs SOAR vs Agentic AI
- Implementation pathways for gradual adoption
- Risk and governance best practices
- Case study: reducing phishing response time by half
- Deep dive: LMNTRIX Artemis and LISA in action
- CISOs and SOC leaders aiming to modernize detection and response
- Security architects exploring AI-driven automation
- Analysts and incident responders seeking to reduce repetitive workload
- Executives evaluating AI’s role in cybersecurity strategy
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