ai · security · skills

Sample consultancy report

Globex: Cloud & Container Security

Where AI has moved into this function, whether the controls kept up, and the one move that earns the next rung. Read in five minutes; decided in one meeting.

Prepared on
The aisecurityskills function diagnostic
Basis
Cloud Security Alliance (CSA) AI Controls Matrix (AICM) · AI Security Maturity Model (AISMM) × AI Cyber Maturity Model (AI-CMM)
Evidence state
Illustrative · fictional organisation
Issued
18 Jul 2026
01

The verdict

Governance ahead of adoption: change process and cloud baselines exist, but drift detection is absent and most container workflows stay human-run.

Globex's cloud and container security function reads at L2.3 governance against L1.3 autonomy: an industrial posture where the gate is open because adoption has not outrun the evidence. Organization Management reaches Defined on a written change process and a maintained configuration baseline. Infrastructure and Governance stay at Repeatable: image hardening and workload isolation are only partial, and named supervision of AI-driven cloud changes is unfinished. What caps the climb is absent automated drift detection. CSPM remediation runs assisted; container image scans, cluster admission policy, and change-and-config review remain largely manual — governance must close those gaps before autonomy claims another rung.

Governance

L2.3

AI Security Maturity Model (AISMM) · how well it is secured

Autonomy

L1.3

AI Cyber Maturity Model (AI-CMM) · how far AI has gone

The gate

Open

margin +0.8 · autonomy inside what governance allows

02

Where this function stands

The whole method in one drawing. Governance runs across, autonomy runs up, and the staircase is the gate: each governance level earned is the autonomy an organisation may responsibly claim.

Globex on the governance-and-autonomy gridGovernance from L1 to L5 across, autonomy from L1 to L4 up. The gate staircase marks the autonomy each governance level has earned. Globex sits at governance 2.3, autonomy 1.3, inside the governed region.Ungoverned: ahead of controlsGoverned: earned autonomyGlobex today · L2.3 / L1.3L1L2L3L4L5L1L2L3L4Governance (AISMM) → each level earned is autonomy allowedAutonomy (AI-CMM) ↑
The gate is the product’s one rule: autonomy must never outrun governance. This function sits at L2.3 governance, which allows autonomy up to L2 — and it runs at L1.3, inside the line. Climbing the wall, not the drop.
03

What was measured

Two ladders, one instrument. Each answer maps to a Cloud Security Alliance AI Controls Matrix (AICM) control; a category claims a level only when that tier is evidenced, and an absent control caps it. The same rule scores every live run.

How well it is secured

L2.3

InitialRepeatableDefinedCapableEfficient

The CSA AI Security Maturity Model (AISMM): every answer maps to an AI Controls Matrix (AICM) control, and a level is claimed only when the tier is evidenced.

How far AI has gone

L1.3

ManualAssistedAugmentedAutonomous

The AI Cyber Maturity Model (AI-CMM): where the human sits in each workflow — in, on, then over the loop. our model · calibrated to SAE J3016.

Organization ManagementL3 Defined · 2 of 4 evidenced

Held below the next tier: CCC-07 absent

Infrastructure Security and ResilienceL2 Repeatable · 1 of 3 evidenced

Held below the next tier: tier 3 not yet evidenced

GovernanceL2 Repeatable · 1 of 2 evidenced

Held below the next tier: tier 3 not yet evidenced

04

Findings

Three, ranked, classified by what leadership does with each: act on a priority, protect a strength, and hold a deliberate choice.

  1. 01Priority

    Drift detection is absent while isolation and hardening stay partial

    Organization Management caps at Defined because automated drift detection across the AI cloud estate is absent. Infrastructure Security stays at Repeatable because image and container hardening and workload isolation are only partial. Those gaps are the board priority: without them, Capable evidence cannot be claimed even though change process and network lockdown already run.

    The exact control ids (for your security and governance, risk and compliance team)

    CCC-07 · I&S-04 · I&S-06

  2. 02Strength

    Change process and configuration baseline reach Defined

    A documented change-management process covers AI systems and cloud configuration, default-deny networking locks down AI workloads, and a known-good configuration baseline is maintained across the estate. Cloud engineers are trained on acceptable use. That floor is what keeps governance ahead of the still-manual adopt average.

    The exact control ids (for your security and governance, risk and compliance team)

    CCC-01 · I&S-03 · CCC-06 · HRS-15

  3. 03By design

    Most cloud workflows stay human while Defined evidence finishes

    CSPM remediation runs assisted; container image scans, cluster admission policy, and change-and-config review stay manual on purpose. Change authorization before go-live is only partial, and named human supervision of AI-driven cloud decisions is unfinished. That restraint is what keeps the gate open with positive margin.

    The exact control ids (for your security and governance, risk and compliance team)

    CCC-04 · GRC-15 · HRS-15

05

The climb

Direction, not a how-to: the next rung, and the governance that must move before autonomy does.

  1. Next quarter

    Stand up automated drift detection against the approved AI cloud baseline and enforce isolation of AI workloads so Organization Management and Infrastructure Security can evidence the next rung.

  2. Two quarters

    Enforce the hardening baseline on AI images and containers, close the change-authorization partial, and name accountable supervision for AI-driven cloud changes so Capable evidence matches the autonomy CSPM is ready to claim.

  3. Continuous

    Hold the change-management process and configuration baseline through each estate change; re-run the diagnostic before lifting image-scan or admission-policy workflows another autonomy rung.

06

About this instrument

What a reader should carry out of the room: how the diagnostic works, how progress is tracked, and what the practice is for.

One questionnaire, two reads

Every answer maps to a Cloud Security Alliance AI Controls Matrix (AICM) control. Read one way, the answers grade the function: governance versus autonomy, joined by the gate. Read the other way, the same answers name the skills each person in the function must acquire. Diagnosis and reskilling from one sitting.

Tracked, not judged

The first run is a baseline, never a verdict. Re-assess after the work and the radar overlays the previous run, so leadership sees movement, not a grade. The compatible-standard packs (ISO/IEC, the National Institute of Standards and Technology, and the CSA AI Consensus Assessments Initiative Questionnaire) are lenses on the same answers: assess once, report many ways.

Direction, not a solution

AI is a moving target, so the report names the next rung and the governance that must move first — never a vendor stack or a how-to. The gate keeps the climb honest: autonomy is claimed only after the controls that catch it are in place.

Derived at build time from the Globex posture config through the live function-diagnostic scorer: the same questions, tiers, and gate every real run uses. A bank change re-derives this sample automatically; nothing here is hand-scored.

Globex is a fictional organisation; the postures are self-assessed sample data, never client results. Nothing in this report is certification, and no standards body has reviewed it.