Governed AI Infrastructure Audit
An AI deployment readiness assessment for organizations putting AI Employees into real work — the infrastructure, the controls, and the operating model, reviewed before the auditors ask.
Book a 30-minute scoping callWhen this is the right engagement
AI is in the building. Some of it was planned. Your dashboards are mostly green. And yet:
- AI agents are already running somewhere in the organization — a pilot, a vendor tool, a team's side project — and nobody can list them all
- Security or procurement has asked who approved what an agent did, and the answer took more than a day to assemble
- An AI deployment stalled between "the demo worked" and "we can defend this" — governance, not capability, was the blocker
- Credentials, customer data and model keys touch AI tooling through paths no one has mapped end to end
- Leadership has set an AI mandate for next year and the platform team cannot say, with evidence, whether the estate is ready to carry it
If three or more of those describe your organization, this engagement is calibrated for you.
What the audit produces
Three deliverables, plus a 90-minute executive readout.
1. Current-state map of the AI estate
A visual and written document of every AI deployment as it actually exists — agents and AI Employees in use, the data and credentials each one touches, where approvals happen (or do not), which environments share which substrate, and who can stop what. Most organizations discover items on this map they did not know they were running.
2. Governance and readiness risk register
Every gap between what a defensible AI deployment requires and what exists today — supervision, a single enforcement point for approvals, audit trail, separation of duties, isolation, kill switches, consent and suppression, key handling — ranked by likelihood × blast radius. Some are urgent. Most are not. All are in the register.
3. Readiness sequence with cost-benefit per item
Written in the language a CFO and a CISO can both read: what to fix before the first governed deployment, what to fix before scale, what can wait, and what each step costs and returns. This is the document you take into the budget conversation and the vendor review.
The 90-minute executive readout walks your senior leadership through all three deliverables and answers questions live. This is included; not a separate engagement.
How the engagement runs
Week 1
Kickoff, access provisioning, and initial interviews with the platform team, security, and the people who actually run or built the AI tooling. I want the operators to tell me what they are worried about before I read a single config.
Weeks 2-3
Inventory and configuration review across environments: every agent and AI Employee, its credentials and data paths, its approval and audit behaviour, the kill switches that exist and the ones that do not. Deeper interviews with engineering, security and procurement.
Week 4
Synthesis. Draft of the current-state map and risk register goes to your team for fact-checking. This is not optional — the deliverables need to be accurate before they are useful, and your reviewers will test them.
Weeks 5-6
(For 6-week engagements.) Readiness sequence drafting, executive readout preparation, final document refinement based on stakeholder feedback. For 4-week engagements this work happens in compressed form within Week 4.
Investment
$55,000–$75,000
Fixed-fee, scope-dependent.
The range reflects the size of the AI estate and the regulatory weight on it. A single business unit with a handful of deployments and one cloud provider anchors at the lower end. Multiple units, regulated data, or several vendors and platforms in play anchor higher.
Engagement length within the four-to-six week range is determined during the discovery call based on scope.
What’s not included
- Implementation of the intervention sequence. The audit produces the readiness sequence. Your team can execute it directly, or I can be retained for implementation advisory at $400/hour, as a fractional CTO retainer ($14,000–$28,000/month), or as a Fractional Chief AI Officer ($25,000–$35,000/month, six-month minimum). This is a deliberate split: the audit needs to be honest about your situation, and that honesty is harder to maintain when the same provider is selling you the implementation work.
- Penetration testing, a SOC 2 or ISO 27001 certification programme, or model evaluation research. These are different engagements with different methodologies. If you need them, I can refer you to specialists.
Who this is for
- Organizations with 50 to 5,000 staff where AI is moving from experiments to real work — agencies, NGOs, regulated mid-market companies, and government units
- Security, legal or procurement review stands between the AI pilot and production, and someone has to bring evidence to that review
- At least one AI deployment already running — a vendor tool, a pilot, or an AI Employee — so the audit has an estate to map, not a plan to critique
- CIOs, CISOs, heads of digital or programme leads with budget authority for an engagement at this scale and the standing to execute on the findings
This is not the right engagement for a solo operator with one agent, a team that has not yet deployed anything, or an organization that already knows exactly what is wrong and needs execution help rather than diagnosis. If that’s you, get in touch anyway and I’ll point you in a more useful direction.
About me
I spent eighteen years at IBM as Senior Managing Consultant and Enterprise Architect, advising Fortune 500 engineering organizations on platform and infrastructure architecture. I now run AIToken Labs, where my own company operates on the same governed AI Employees the audit tests for — supervised by trust level, gated at one enforcement point, stamped with the authority each action ran under. The audit methodology is built from two decades of enterprise architecture and from running the thing myself, which is why the deliverables read like something a reviewer can check rather than something a vendor can claim.
Next step
The audit starts with a 30-minute scoping call. The call is free. Its purpose is to confirm that your situation fits what I work on, and to scope the engagement length within the four-to-six-week range so that we can issue a fixed-fee proposal.
What you bring to the call: a rough sense of how many AI deployments are running or planned, who owns them, which review (security, legal, procurement) stands between them and production, and what has stalled so far. I do not need access to systems or detailed information at this stage.
If a call isn’t the right format for an initial conversation, you can also reach me directly at kayode@anthonyodole.com.
Frequently asked
- How is this different from the Governed AI Employee checklist?
- The checklist is a free document that says what a defensible AI deployment requires and how one platform answers it. The audit is four to six weeks of looking at your organization specifically — what is actually running, what it touches, what would survive a review — and a sequence for closing the gaps. Read the checklist first; if it raises more questions than it answers about your own estate, that is what the audit is for.
- We have a 30-day pilot on offer at AIToken Labs. How does the audit relate to it?
- The pilot deploys one AI Employee in one department under full supervision and ends with a handover. The audit looks at the whole estate. Most organizations do the pilot first; the audit is the step after, when the question changes from "does this work here" to "is the whole organization ready to run this at scale".
- Can you do the implementation work after the audit?
- Yes, but as a separate engagement. The audit price is fixed; implementation is advisory at $400/hour, a fractional CTO retainer, or a Fractional Chief AI Officer engagement. This is a deliberate split: the audit needs to be honest about your situation, and that honesty is harder to maintain when the same provider is selling you the implementation work.
- Our organization is smaller than the floor. Should I still reach out?
- The floor is about engagement economics, not whether you have something worth reviewing. If you are smaller and an AI deployment is already producing risk you cannot absorb, reach out. I will tell you honestly whether the pilot, the checklist, or a shorter review is the right shape.
- How do you handle confidentiality?
- NDA before the discovery call if you want one; mutual NDA standard before any engagement. The audit deliverables are yours and remain yours. I do not publish client-specific findings, and the AI Employees on the platform I run are governed by the same controls the audit tests for.
Want more context before booking? Read the article series →