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.

This paper makes that case plainly. It assumes AI delivers real capability gains,  in context assembly, triage, investigation enrichment, response recommendation  and asks 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.

Shift 1 AI transforms MDR economics

AI-enabled MDRs can now deliver greater cost efficiency and more personalized service simultaneously — a combination previously impossible to sustain at a realistic price point.

Shift 2 AI shifts the governance question

"Who runs the SOC?" becomes "Who owns decisions when machines are making them?" Decision ownership is the new baseline evaluation criterion.

Shift 3 AI blurs the tool/service boundary

Deploying an AI SOC tool is not just a technology decision — it is a whole operating model commitment. Wrong choices create technical debt that is expensive to unwind

THANKS TO DAYLIGHT SECURITY