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GovernIT Consulting Inc.
We turn stalled projects into delivered value through governance discipline, independent oversight, and hands-on execution.
We turn stalled projects into delivered value through governance discipline, independent oversight, and hands-on execution.
Clear rules, approved tools, trained people, and a small number of workflows that save hours you can actually count. Installed in weeks, then handed to your team to run.
Someone in your organization pasted a client document into a chatbot this week. Probably several people, probably through a personal account, and probably because it worked.
You do not have a list of which tools are in use, who owns them, or what has gone into them. And you cannot point to a single hour saved, because nobody set a baseline to measure against.
So you are carrying the exposure of adoption without the return on it. That is the worst of both positions, and it is the most common one.
This page is for you if: your staff are using AI faster than your policy can keep up, you are being pitched AI tools you have no way to evaluate, or you have been told AI will save time and cannot find the evidence in your own numbers.
Rules, Tools and Results, In That Order
Five phases, each with defined entry criteria, fixed deliverables and exit criteria that have to be met before the next one starts.
One to two weeks
Diagnose
The AI Readiness Audit. We interview across operations, client-facing teams and IT, inventory the tools actually in use including the ones nobody approved, find the six to ten workflows where time is genuinely lost, and score you across seven domains. You get a maturity scorecard, three to five costed opportunities and a ninety-day roadmap. Fixed fee, and it stands on its own if you go no further.
Design
We agree on the posture, the policy scope, the data that never goes near a model, and which two or three workflows get built, with acceptance criteria written down. It ends in a memo your sponsor signs. No sign-off, no build.
Two to four weeks
Establish
We publish the acceptable-use policy and the no-go data card, stand up the intake form, approval workflow and tool register with named owners, run one real vendor review end to end as a worked example, build the selected workflows with human checkpoints, and record the measurement baseline.
Embed
We train your people on their own tasks, not on generic prompts. Runbooks for every workflow, and coaching for the named owners. Then the adoption check, which is three questions any member of your staff should be able to answer without looking anything up: What can I use AI for? What can I never share? How do I request a tool? If they cannot, we are not finished. Then a formal transition sign-off.
Quarterly, optional
Sustain
We re-score the domains, review the register and any incidents against baseline, refresh the approved-tools list as the market moves, and give your sponsor an independent read. The tool landscape changes every quarter. Part of what this buys is somebody else keeping up with it.
At some point your board, your partners or your regulator will ask what your organization is doing about AI. That question is coming, and the honest answer today is probably a shrug and an anecdote.
The difference between an executive who looks in control of this and one who does not is not how much AI they have deployed. It is whether they can hand over a document: what is in use, who owns it, what rules apply and what it has actually saved. Ninety days from now that document either exists or it does not.
The question is coming. The document takes weeks.
There is no single correct posture, so we make the choice explicit and put your sponsor’s name on it. Our default is enablement with guardrails: usage is encouraged inside clear boundaries, enforcement starts with training rather than blocking, and controls tighten as the risk rises.
That works because every tool and every vendor gets a risk tier.
Anything unclear defaults to the higher tier until it is proven otherwise.
The point of tiering is speed, not caution. Most requests are genuinely low risk, and if they are treated with the same ceremony as the dangerous ones, your staff will stop asking and go back to personal accounts.
We aim for a capability that is properly defined and consistently practised, with depth added where it pays back. We do not promise a best-in-class AI operation, because over-promising is how AI programmes talk themselves into a backlash.
“AI risk management offers a path to minimize potential negative impacts of AI systems, while also providing opportunities to maximize positive impacts.”
National Institute of Standards and Technology, AI Risk Management Framework 1.0, 2023
Which is why the posture is a decision your sponsor signs, and why low risk moves fast.
We do not give legal advice.
Where the work touches contract wording, intellectual property clauses or how a regulation applies to you, your counsel reviews and owns that. It is written into every report and policy we produce, and we would rather say it early than have it discovered late.
We do not become your AI department.
Tool and workflow ownership transfers to named people on your side at Embed, and that gate is written down before we start. We install and assure the capability. We do not operate it.
We will tell you when the answer is not yet.
If the underlying process is too chaotic to automate, the Audit says so and stops there. Automating a broken process just produces broken output faster.
And we are the wrong firm for you if you would rather not know.
The first thing we do is inventory what is actually in use, including the tools nobody approved. Some organizations do not want that written down. That is a reasonable preference and an honest reason not to hire us.
Is this just an old-fashioned PMO with a new name?
Fair question, and usually the answer would be yes. What separates the two is decision rights, defined health criteria and thresholds agreed before anything goes wrong. Those are the things that let a function change an outcome rather than describe one. If your PMO already has all three, you do not need us. Most do not, which is precisely why most get cut in the first hard budget cycle.
Will you run the PMO for us?
No. We install and assure PMOs, we do not staff them. If we ran it, you would have rented a PMO, and it would leave when we did.
We built one before and it became overhead.
Most do, because they were built to report rather than to decide. The test of ours is whether decisions change: whether leadership funds, fixes or stops differently because of what the function shows them.
We genuinely do not have the people.
Then we can arrange managed staffing through a partner, under our governance and our operating model, time-bound with a transition plan back to your own people. It is a bridge, not a destination, and we will say so in writing.
Do we need new tools?
No. The framework is tool agnostic and works with what your teams already use. If a gap shows up in the Diagnostic we will name it, but we do not arrive with a product to sell you.
What if one of our projects is already in serious trouble?
That project needs a review of its own, which is Project Salvage. The portfolio needs this. The two are designed to meet in the middle.
How long before it stands on its own?
The Diagnostic answers that for your organization. Every phase has a defined exit, so “done” is written down before we start.
What does it cost?
The Diagnostic is a fixed fee, agreed before we start. The Build is fixed scope, priced from what the Diagnostic finds. No hourly billing, and no open-ended consulting meter.
Thirty minutes will tell you whether you have a problem worth fixing.
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