How do I prepare my company for AI?
Audit which workflows touch sensitive data, decide what can never be sent to a third-party model, add a human review step before any AI-drafted client output ships, and measure a small number of clear success signals.
Start with workflows, not tools
Pick three to five repeating tasks where speed or quality matters. For each, write down the inputs, the outputs, and where mistakes would cause real harm.
Define data boundaries
Decide what kinds of information may never be sent to an outside model — client PII, financial records, legal matters, health information, anything under NDA.
Put a human review gate before client-facing output
Any AI-drafted email, contract, deliverable, or external message should pass through a named human before it leaves the company.
Measure a small set of signals
Time saved, error rate caught at review, and how often the team rolls back to the non-AI version. Three is enough.
When to use this
- You have a small team trying multiple AI tools without a shared standard.
- You handle client data and want to use AI without leaking it.
- You want repeatable AI workflows you can hand off cleanly.
What to avoid
- Rolling out an AI tool company-wide before defining what it should and should not touch.
- Treating LLM output as authoritative without a review step.
- Promising customers AI-driven outcomes you cannot measure.