How to prepare your company for AI
This guide is for leaders trying to use AI tools usefully without leaking client information or shipping wrong answers. It is built for action, not theory.
What AI readiness means
AI readiness is the state in which your data, workflows, review gates, and policies make it safe and useful for your team to use AI tools.
What to audit first
Walk through the work that fills your calendar. Note which tasks touch client data, financial records, legal matters, or anything under NDA.
- List the three to five highest-frequency repeating tasks on your team.
- For each task, write the inputs, the outputs, and the failure mode if it ships wrong.
- Flag every task that touches sensitive data.
Data and privacy boundaries
Decide what kinds of information may never be sent to a third-party model. This becomes a one-page policy your whole team can reference.
- Write the do-not-paste list: PII, credentials, NDA material, regulated data.
- Pick one approved tool per category (drafting, summarization, search) so 'which tool' is not a daily decision.
- Document the contractual privacy posture for each approved tool.
Workflow opportunities
Start with drafting, summarization, and structured-data extraction inside boundaries you control. Avoid customer-facing autonomy in the first ninety days.
Human review gates
Any AI-drafted client-facing output should pass through a named human before it leaves the company. Make this a step in the workflow, not a hope.
Analytics and success measures
Pick three metrics: time saved, errors caught at review, and how often the team rolls back to the non-AI version.
Where companies get AI wrong
Pretending an LLM 'knows' facts, skipping review on client-facing output, and treating AI rollout as a tools decision instead of a workflow decision.
How BPM can help
BPM Consulting works with teams on AI readiness, workflow design, and the operating system around adoption. No guarantees of outcomes — just clearer systems and fewer avoidable mistakes.