AI SOC RESEARCH

 AI SOC vendors promise autonomous investigations, analyst replacement, and human-less operations. Practitioners report enrichment tools, shallow pilots, and AI kept away from most critical tasks that matter. Based on 30+ vendor interactions, practitioner interviews, and SOC community OSINT, this paper examines why that gap exists,  and why vendors keep explaining it away. 

Key takeaways

• AI SOC is at 1-5% market adoption. The revolution is not here yet.
• AI is delivering real value in enrichment, summarisation, and alert volume reduction, but not autonomous decision-making.
• When adoption stalls, vendors reframe it as buyer readiness or trust deficits rather than product immaturity. This is the When Prophecy Fails pattern.
• Practitioners are not resistant to AI. They are applying professional skepticism earned through SOAR, UEBA, and XDR hype cycles.
• Five recurring architectural failures explain most negative outcomes: misrepresented classification, binary decisions in probabilistic domains, tight coupling to irreversible actions, premature autonomy, and insufficient context.
• The paper includes a nine-question buyer framework for evaluating AI SOC claims on operational grounds.

The AI SOC will arrive, but not through marketing momentum.