Your company adopted AI.
Does it operate it?

If you are in the 84%, you do not need another pilot. You need answers.

1. What AI is actually running in my company, sanctioned or not, and what is it touching?

   Most companies can name two or three tools and miss a dozen. A real inventory surfaces every model, agent and integration in use — sanctioned or shadow — and maps what data each one touches. You cannot govern what you have not found.

2. What is it returning, measured in money and hours, not in vibes?

   Productivity gains reported in surveys are not ROI. We instrument the workflows AI touches and measure cycle time, error rate and cost per task against a real baseline, so the number you take to your board survives scrutiny.

3. What rules govern it — and are they enforced in the systems themselves, or just written in a PDF nobody reads?

   Most AI policy lives in a PDF and stops at the door. Enforced governance means the rules run as code in the path of execution: access controls, data boundaries and audit trails that hold whether or not anyone remembers the policy.

4. When it fails — and it will fail — who sees it first: my team or my customer?

   If your customer is your alerting system, you do not have observability. Agentic systems fail quietly: drift, degraded output, silent retries. Instrument for that specifically, with thresholds and on-call ownership, and failures surface internally first.

5. Where does my data physically live, and who else can reach it?

   Data sovereignty is a buying criterion in Mexico, not a checkbox. Know which region each provider processes and retains in, what subprocessors sit behind them, and what your contract actually permits — before it becomes a procurement problem.

Data sovereignty is not a compliance checkbox. It is a buying criterion — and most consultants selling AI have no answer for it.