Everyone Wants AI. Nobody Agrees on How to Do It Safely.

What inaction is costing you

• Competitors are already deploying AI in workflows that used to require 10 people
• Your best talent is evaluating whether to stay at a company that isn't investing in modern tools
• Every month without an AI strategy is a month of data and operational insights you're not capturing
• When pressure forces a rushed AI adoption, the risk goes up and the ROI goes down

What moving too fast costs you

• Customer data sent to an AI model without proper data handling agreements exposes you to regulatory risk
• AI that hallucinates in a customer-facing or financial context produces liability, not value
• A $200K AI platform purchase with no defined use case produces $200K in sunken cost and politics
• A failed, high-visibility AI initiative makes the next one harder to fund and politically harder to sponsor

Your deliverables

• A risk-mapped list of AI use cases relevant to your business — what's safe to start now versus what needs governance first
• An honest ROI assessment: which use cases have a defensible business case and which are still speculative
• A plain-English policy framework you can put in front of legal without a technical translator
• A written 90-day AI adoption plan — specific enough to assign owners and begin immediately

How it works

1. Pay $999 to secure the slot.
2. Intake within 24 hours — a short email asking exactly what I need.
3. Delivery within 3 days — a written output you can act on immediately.

You don't need to know which AI tools you want. You need to know what problem you're trying to solve. Bring that, and we'll build the rest from there.

What are the real risks of enterprise AI adoption?

The main risks are data leakage (sending customer or proprietary data to external models), compliance violations (HIPAA, GDPR, SOX), model hallucinations producing bad business decisions, and vendor lock-in. The key is mapping which risks apply to your specific use cases before selecting tools or vendors.

How do you calculate ROI on AI investments?

Start by measuring the cost of the manual process you're replacing. If AI replaces $500K in labor and costs $80K per year to run, the ROI case is clear. If you can't name the specific process it replaces, you don't have a business case yet — you have a technology looking for a problem.

How fast can AI actually be deployed in an enterprise?

Low-risk internal use cases — writing assistance, document summarization, code suggestions — can go live in weeks. Customer-facing or regulated use cases require compliance review, which typically adds 3–6 months. Speed depends entirely on the use case and your regulatory environment.

What should we do before talking to AI vendors?

Define the problem you want to solve before evaluating solutions. Most enterprises that struggle with AI adoption started by buying a platform and then looking for problems to solve with it. That's backwards. Start with a specific, measurable business outcome — then find the tool that addresses it.