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A 10-step AI opportunity review for your business

For owners who are not sure where AI would actually pay off. It starts with the process that loses money — not with choosing a model.

Start with economics, not a model

The useful question is not “Which AI tool should we buy?” It is “Where does a repeatable process lose revenue, margin, time or customers — and which actions can be delegated safely?”

  1. Choose an outcome. Define one measurable result: faster response, fewer

missing documents, shorter cycle time or recovered opportunities.

  1. Find a recurring flow. List the enquiries, orders, invoices, documents,

tickets or decisions arriving every day.

  1. Trace one item end to end. Record every hand-off, system, wait and approval.
  2. Price the friction. Estimate volume, delay, error rate, labour and revenue

at risk. Mark assumptions clearly.

  1. Separate actions from decisions. AI can read, classify, extract, draft and

reconcile. Commitments, payments and unusual exceptions normally stay human.

  1. Identify sources of truth. Decide which CRM, ledger, contract or inbox is

authoritative when records disagree.

  1. Set permissions. Write three lists: autonomous actions, approval-required

actions and prohibited actions.

  1. Create evidence. Log the source, rule, action, timestamp and outcome. A sent

email is not a reply and a detected issue is not recovered cash.

  1. Run a narrow pilot. Use one workflow, a limited volume and a 30-day window.
  2. Scale only what works. Connect the next stage after the first outcome is

evidenced.

Your first-process worksheet

Write down:

Next step

Evolvin can turn this worksheet into a first-process map covering the agent, integrations, controls and pilot metrics. The best starting point is a result you can verify within 30 days.

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Next step

We can run this review on your own numbers and show where the first agent pays off.

Request a first-process map

This material is a method, not a promise of a result. Any figure in your case is measured before and after — not assumed.