Headline figure
57%
do not have an AI adoption strategy
Source: SOC Maturity Report 2026, SOC-CMM® (CC BY-SA 4.0), soc-cmm.com. AI section: adoption strategy, AI types, taker/shaper/maker approach and perceived value.
AI in the SOC: 2026 SOC-CMM statistics
AI in the SOC in 2026: 57% have no adoption strategy, co-pilots grow 145%, agents 118% and perceived value remains limited.
Executive reading
AI adoption in the SOC grows strongly but without governance: 57% of SOCs lack an adoption strategy defining tasks to augment or replace, risks, guardrails and alignment with the corporate AI policy. Usage spreads across off-the-shelf LLMs (35%, +55%), generative AI (33%), customised LLMs, co-pilots and embedded AI (27% each) and agents (18%). The strongest growth is in co-pilots (+145%) and AI agents (+118%). The report's conclusion is sober: current perceived value is limited, across all delivery models.
What does this mean for your SOC? The gap between adoption and value is now the most important figure. 65% of SOCs are takers (using unmodified LLMs), 20% shapers and 15% makers, and the majority expectation is a medium role: AI as a supporting tool that takes over some tasks, not a transformation. The mature reading is anti-hype: define candidate tasks, sensitive data, guardrails and value metrics before scaling. The AI assurance service evaluates exactly that: whether your SOC's AI is governed like any other critical control.
Report data
| Metric | Value | Reading |
|---|---|---|
| No AI strategy | 57% | Majority of dataset. |
| Taker / shaper / maker approach | 65 / 20 / 15 | Share of SOCs per integration approach. |
| Off-the-shelf LLM | 35% | +55% YoY; most common type. |
| AI co-pilots | 27% | +145% YoY; the largest growth. |
| AI agents | 18% | +118% YoY; emerging adoption. |
Analysis and context
Methodology: the figures come from the 2026 SOC Maturity Report survey (late January to mid-March 2026; 290 responses, roughly 200 retained after cleaning). This edition expanded the AI questions to capture real adoption and satisfaction, and the report recalls that the SOC-CMM model is driven by best practices: AI still has a limited footprint in the model precisely because those best practices remain scarce.
The distribution by type shows more balanced adoption than in 2025, when generative AI dominated the answers. In 2026, off-the-shelf LLMs (35%), generative AI (33%), customised LLMs (27%, +64%), co-pilots (27%, +145%), AI embedded in existing tooling (27%, +23%), agents (18%, +118%) and supervised machine learning (16%) coexist. Adoption is diversifying faster than it is being governed: more than half the market is moving without a formal strategy.
On value, the report is explicit: many SOCs see limited value in their current implementations, with only minor differences between in-house, MSSP and hybrid SOCs, and there is a clear gap between potential and actual value. The most voted future expectation is a medium role for AI: support plus absorption of some tasks. How this evolution fits the model is explained in AI and automation in SOC-CMM, and the broader market context can be cross-checked against the 2026 AI in cybersecurity statistics.
What to do with this data
- Define a SOC AI strategy before expanding use cases.
- Separate taker, shaper and maker approaches.
- Protect sensitive data.
- Measure real value against noise.
- Require traceability of AI-assisted decisions for audit.