The DATA-driven advisory firm

AI fundamentally changes the value equation in security operations , but not in the way most vendor narratives suggest.

Organizations that have built AI into the core of how they detect, investigate, and respond can now deliver expert-grade analysis, personalized to any environment, at a price point that is realistic. Security organizations that have bolted AI onto legacy architectures cannot.

In this paper we make that case plainly. We  assume AI delivers real capability gains, whether in context assembly, triage, investigation enrichment, response recommendation,  but we ask a more useful question: who is best positioned to realize those gains for you?

For those with the staff and expertise to govern AI decisions directly, an internal AI SOC may be the right model. For others, especially those without a mature internal SOC,  the answer may be an AI-native MDR. For many, a hybrid approach is most realistic. 

What this paper argues is that the operating model decision is now the most important security operations decision a CISO makes. Most organizations are making it by default, through tool purchases and MDR renewals, without the framework to make it deliberately. This paper provides that framework.

Three core shifts 

Shift 1 AI transforms MDR economics

Expert-grade service at a price point previously out of reach. Force multipliers, not replacements.

Shift 2 AI shifts the governance question

"Who runs the SOC?" becomes "Who owns decisions when machines are making them?"

Shift 3 AI blurs the tool/service boundary

Deploying an AI SOC tool is an operating model commitment. Wrong choices create expensive technical debt.

THANKS TO DAYLIGHT SECURITY