AI Advisory
AI that pays for itself, rolled out without exposing your business.
Your team is already using AI. The only question is whether it is happening with guardrails or in a browser tab nobody told you about. AI advisory is about getting the value deliberately instead of absorbing the risk accidentally.
Find where it actually pays
Most AI projects fail because they start with the tool instead of the work. We look at where your people spend hours on something repetitive, structured, and low-judgment, and target those first. Quoting, intake, documentation, summarizing, drafting. Boring wins that give hours back.
Your team is already using it, on their own accounts
This is not a prediction. In the 2026 Verizon Data Breach Investigations Report, 45% of employees were regular users of AI on their corporate devices, authorized or not, up from 15% the year before. Of the people accessing AI services from company hardware, 67% were doing it through non-corporate accounts. That is a tripling of usage in a year, most of it running through personal logins your business has no visibility into and no agreement with. Blocking it does not work. Knowing about it does.
Source: Verizon 2026 Data Breach Investigations Report, AI usage, p.13
Understand what you are handing over
Every AI tool your team touches is a place your data can go. Which vendors train on your inputs, which retain them, which are covered by your existing agreements, and which quietly are not. Most businesses have never asked, and the answers change what you should allow. The risk is not only the model. It is the account, the plan tier, the retention setting, and who at the vendor can see what was pasted in.
Risk can emerge both from third-party data, software or hardware itself and how it is used.
Write the rules before you need them
A short, readable AI policy your team will actually follow: what tools are approved, what data may never be pasted into them, what has to be reviewed by a human before it goes out the door, and who to ask when it is unclear. One page beats a binder nobody opens.
Roll it out like a project, not an experiment
Pick the use case, define what success looks like, deploy to a small group, measure whether it actually saved time, then expand or kill it. AI that turns your business into a science project is worse than no AI at all.
What's included
- AI readiness and opportunity assessment
- Use-case identification tied to hours and cost
- Vendor and data-handling review
- Written acceptable-use policy for AI tools
- Microsoft 365 AI capability configuration and governance
- Pilot design, rollout, and measurement
- Team training on safe and effective use
- Ongoing review as tools and risks change
Common Questions
AI Advisory, answered straight.
How many employees are actually using AI at work?
More than most owners think, and the number moved fast. The 2026 Verizon Data Breach Investigations Report found 45% of employees were regular AI users on their corporate devices, up from 15% the year before, and that 67% of people accessing AI services from company hardware did so through non-corporate accounts. The practical read is that the decision about whether your business uses AI has already been made by your staff. What is still open is whether it happens on accounts you can see.
Is our data safe if employees use public AI tools?
It depends entirely on the tool and the plan you are on. Some consumer tiers retain inputs and use them for training. Business and enterprise tiers of the same product often do not. Most organizations have never checked which one their team is using, and that is usually the first thing worth fixing.
Is our business too small for AI to matter?
No. Smaller organizations often see the clearest return, because a few hours a week saved is a meaningful percentage of a small team. The work is picking the right one or two use cases instead of trying to transform everything.
Do we need to buy new AI software?
Often not. A significant amount of usable capability is already included in tools you are paying for, most commonly Microsoft 365, and simply is not turned on or configured. We look there before recommending new spend.
The rest of the stack.
These are not separate contracts with separate vendors. They are parts of one engagement.
Managed IT
Most small and mid-size businesses do not need a full-time IT hire. They need someone who already knows how the environment is built, watches it constantly, and picks up when something breaks. That is what this is.
Read more →Cybersecurity & Compliance
There is no cheaper version of Apex where we quietly leave the security out. Patching, multi-factor authentication, endpoint protection, email defense, and monitoring are part of every engagement, because an environment without them is not managed, it is just watched.
Read more →Infrastructure & Continuity
Most environments we inherit were not designed. They accumulated. A server added here, a switch added there, a cloud service someone signed up for, and nobody holding the whole picture. Infrastructure work is about replacing accumulation with architecture.
Read more →Where We Work
AI Advisory across North Texas and southern Oklahoma.
Supported remotely wherever you are, and onsite across the Texoma region and the Collin County corridor.
Let's talk about where you stand.
We will find the gaps, tell you which ones actually matter, and give you a clear plan. Every inquiry gets a response the same business day.