AI Governance Consultant for Policies, Access, and Safe Rollouts
Ship AI that legal, security, and operators can live with. Policies, access, and a rollout plan, not a slide about principles. Zack works with companies nationwide across the US, remotely or in person.
Outcomes that survive real users
- PolicyWritten acceptable use the staff can follow
- AccessWho may use which tool, on which data
- RolloutA first approved workflow, not a company-wide blast
- Policy
- Written acceptable use the staff can follow
- Access
- Who may use which tool, on which data
- Rollout
- A first approved workflow, not a company-wide blast
Direct answer
What this page is about
Zack Shields is an AI governance consultant who writes usage policies, sets access controls, and runs a secure first rollout. He works nationwide across the US, remotely or in person. A focused program is quoted in the published $2,500 to $15,000 project range.
Key facts
- Zack Shields, independent consultant in Orlando, FL
- Hours: Monday to Friday, 9:00 AM to 6:00 PM Eastern Time
- Contact through the free workflow review form
- Works with companies nationwide across the US, remotely or in person
- $2,500 to $15,000 for typical project builds
- Free 30-minute workflow review
- Usage policy in plain language
- Access by data class
- One approved first workflow
Last updated
Buying another tool is easy. Building a system to write a usage policy and access model the team can actually follow is the work.
AI Governance Consultant for Policies, Access, and Safe Rollouts only pays off when the system watches real work, catches exceptions, and leaves humans the judgment calls. For operations teams that means stop unofficial ChatGPT use and unused "AI programs" that nobody can defend. What they often get instead is a dashboard nobody trusts, a chatbot that creates tickets, or a pilot that never becomes the default path. I build the closed loop so your team only touches what needs a person.
AI governance is the work that decides whether a company can use models without creating a second, unofficial company in people's browsers. I am Zack Shields. I help owners write usage policies, set access controls, and run a secure first rollout. I work with companies nationwide across the US, remotely or in person.
This is not a Big Four program and not a 90-page risk register. The deliverable is a short policy people will follow, a list of approved tools and data classes, and one workflow that is allowed to go live. If the first job is a labor sink with no policy question, start on the AI automation consultant page. If you need part-time technical leadership across vendors and hiring, start on the fractional CTO page.
I come to this from implementation, not from a compliance product. I have shipped automations that touch customer records, clinic intake, and money-adjacent operations. The governance work exists so those builds can survive a security review and a bad week.
What unofficial AI use actually costs
Staff already pasted customer records into a consumer chat window. Nobody wrote down what is allowed. When a buyer or an insurer asks for the policy, the honest answer is "we told people to be careful." That is not a control.
The opposite failure is a freeze. Legal bans every tool. Operators keep using them on personal phones. You get the risk of shadow use plus the cost of an official program that does no work.
The third failure is access with no job. Everyone gets an enterprise seat. Prompts are not reviewed. Plugins can read the shared drive. A model with too many tools and no allow-list is not "innovation." It is an unreviewed integration.
Write the rules before the next unofficial paste
Request a free 30-minute review. Bring who is already using AI and what data they touch. You leave with a candid read on whether you need a policy, a build, or both.
What an AI governance engagement includes
Short documents, named owners, and one approved path to production.
- 01
Acceptable use policy
A one-to-three page policy in plain language: what staff may paste, what must stay out, which tools are approved, and how to ask for an exception. Written for the people who do the work, not only for the binder.
- 02
Access and data classes
Who may use which model, on which class of data, with which logging. Customer records, health information, payment data, and internal strategy get different rules. Credentials live in your accounts, not in a shared password note.
- 03
Tool allow-list and vendor notes
A short list of approved products and what each is for. Consumer apps that are not on the list are out of policy. I do not sell a vendor. I write down what you already chose and what should wait.
- 04
First secure rollout
One workflow that is allowed to go live under the policy: the prompt or agent, the review step, the retention rule, and the person who can shut it off. Governance without a first live path is just a freeze with better stationery.
What I put in an AI usage policy
Data classes beat a single "be careful" line
A useful policy names classes: public marketing copy, internal ops notes, customer identifiers, health information, payment data. Each class has a default: allowed in an approved workspace, allowed only after redaction, or never. Staff can follow a table. They cannot follow a vibe.
I keep the table short. If every row needs a lawyer to interpret, the policy will lose to a personal phone on a busy Thursday.
Access is a list of tools, people, and logs
Who may use the consumer app, who may use the API, who may connect a plugin to the shared drive. Those are three different risks. The access list says so. Logs say who did what. If you cannot answer "who exported last week's tickets into a model," you do not have control yet.
Credentials stay in your identity provider or a secrets store you own. Shared "team" passwords in a chat thread are out of policy, including mine.
The first rollout is a workflow, not a town hall
A company-wide "we are now an AI company" email creates demand you cannot support. The first rollout is one job: a drafted reply, a classified ticket, a redacted summary. It has a reviewer, a retention rule, and a person who can turn it off.
After thirty days we ask whether people followed the policy and whether the workflow earned the next one. That review is part of the engagement.
What a usable governance program changes
Security and operators can agree
The policy is short enough to train in one meeting. Exceptions have a path. You are not choosing between a ban and a free-for-all.
The first build can pass review
When we later automate a labor sink, the access model already exists. The build does not restart the argument about whether AI is allowed.
Shadow use has a place to go
Staff can request an approved tool instead of hiding a personal account. You see the demand instead of discovering it in an incident.
You can answer a buyer or auditor
There is a dated policy, an access list, and a named owner. That is the difference between "we use AI" and "we can show how."
How a governance engagement runs
Most first programs fit in two to four weeks of calendar time, with a lighter writing load than a full audit firm package.
- 011
Free 30-minute review
Tell me who is already using AI, what data they touch, and who will own the policy. I will tell you whether you need governance now, a build now, or both in sequence.
- 022
Inventory and risk notes
List the tools in use, the data classes, and the jobs people are already doing. No invented residual-risk scores. Plain notes a security lead can mark up.
- 033
Policy, access, and allow-list
Drafts you can edit. We walk them with the person who will enforce them. If a rule cannot be followed on a Tuesday afternoon, we rewrite it.
- 044
Approved first workflow
One live path under the new rules, plus a 30-day review. Then you can add the next workflow without rewriting the constitution.
Why this sits with an implementer, not only a policy shop
I write governance that has to survive a real build. A policy that forbids every useful write will be ignored. A policy that allows every write will fail the first security review. The useful middle is a list of allowed actions and a human step for the rest.
I also keep the program small. You do not need a steering committee of twelve to approve a lead-response draft. You need a named owner, a data class list, and a way to say no.
What you get
- Usage policy in plain language
- Access controls by data class, not by slogan
- Secure first rollout with a shutoff owner
- Nationwide, remote or in person
- Same operator who can later ship the automation
- No invented maturity scores or residual-risk theater
Independent governance consultant vs freeze vs Big Four program
Three common responses to unofficial AI use. The useful one is a short policy plus one approved path.
Aspect
DIY / off-the-shelf
Working with me
Speed
A freeze that lasts until the next incident
A followed policy and one live workflow in weeks
Document size
A 90-page register nobody opens
A short policy, an access list, and an exception path
Who can enforce it
Legal only, so operators ignore it
A named operations owner plus security markup
Next step after the paper
Another workshop
An approved first workflow, then automation if the sink is real
Best for
Firms that need a formal attestation letter
Owners who need rules the staff will actually use
Frequently asked questions.
What does an AI governance consultant do?
An AI governance consultant writes the rules for how a company may use models: what data may be pasted, which tools are approved, who has access, and how the first workflow goes live. The deliverable is a followed policy and one approved path, not a principles poster.
Do you sell a GRC platform?
No. I use the docs, identity, and logging you already have when they can hold the job. A new platform appears only when the access model cannot live in what you run today.
How is this different from AI automation consulting?
Automation consulting ships the labor-sink system. Governance consulting writes the policy and access model so that system, and the unofficial use already happening, can be defended. Many clients do governance first, then a build.
How much does AI governance consulting cost?
A focused policy, access list, and first-rollout plan typically lands in the same published $2,500 to $15,000 project range as other scoped work. You get a fixed quote before the writing starts. The 30-minute review is free.
Do you work with companies outside Florida?
Yes. Governance work is mostly remote: interviews, document review, and a working session with security and operations. I work with companies nationwide across the US, remotely or in person.
Will you claim we are certified or audit-ready?
No. I will not invent a certification, a residual-risk score, or an audit letter. I will leave you with dated documents and a named owner. If you need a formal audit, that is a different hire.
What if staff already use personal ChatGPT accounts?
That is the usual starting point. We write what must stop, what may move to an approved tool, and how to request an exception. A ban with no approved path just hides the use.
Ask them in a free workflow review
Tell me the process. I will reply within one business day with a time for a 30-minute call. No pitch.
About your consultant.
I am Zack Shields. I build agentic systems for mid-market and enterprise teams in hospitality, travel, healthcare, and finance. Closed-loop workflows that monitor data, surface true exceptions, route decisions, and act so your team only handles what requires judgment.
My background is operations first, technology second: real estate operations, hospitality systems, short-term rental workflows, sales operations, dashboards, RAG tools, API integrations, and team training. That mix matters because the hard part is rarely the model. The hard part is designing a system people trust enough to use. One that survives real users, edge cases, and daily reality.
When you work with me, you get an operator-builder hybrid who can map the workflow, design the agentic loop, build the system, test the edge cases, document the process, and support adoption after launch.
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Getting started is simple.
The first step is a no-obligation 30-minute workflow review. We map your actual workflows, identify high-leverage agentic opportunities, and give you an honest picture of fit. No pitch.
- 01
Book your call
Schedule a focused conversation about the workflow you want to improve.
- 02
Share your challenges
Walk through the systems, users, exceptions, and reporting gaps that shape the work.
- 03
Get your roadmap
Leave with practical next steps for discovery, pilot scope, or implementation.
Write the rules before the next unofficial paste
Request a free 30-minute review. Bring who is already using AI and what data they touch. You leave with a candid read on whether you need a policy, a build, or both.
- Free
- Cost
- 30 min
- Length
- None
- Pressure