Here is how an AI Opportunity Study reads a business — in this case a composite example, a regional office-supply distributor. We look across the everyday work that quietly consumes staff time, weigh each one, and say plainly which is worth building first. Nothing far off — practical things we can stand up today.
A composite, illustrative example, used to show the kind of work a Study surfaces. Real engagements use your business and your numbers.
Orders and RFQs land as messy email — a list in the body, a forwarded spec, a PDF. A rep retypes it, checks the price book, and writes the quote. It's slow, and it's easy to fumble a line or a price.
A workflow that reads the email and any attachment, pulls the line items, matches them to the current price list, and drafts the quote for a rep to glance over and send. Anything it can't match cleanly, it flags instead of guessing.
Quotes out in minutes, not the next morning. Reps spend their time selling, not retyping — and fewer pricing slips reach the customer.
Illustrative — a sample order email turned into a priced quote in seconds.
Customers call to reorder or chase an order after hours and over lunch — and reach voicemail. Some don't call back. They call whoever picks up.
An AI line — that's Alex — that answers every call, takes a reorder or a message, books a callback, and emails the details to the right rep. It speaks naturally and reads the details back to confirm.
No missed orders, no after-hours staffing. The routine calls are handled; the team only gets pulled in for the exceptions.
The service inbox fills with the same questions — "where's my order," "is this in stock," "what's my price on this." Each one is a small interruption and a context-switch for the team.
A workflow that reads each email, pulls the answer from the order and product data, and drafts a reply for a person to approve and send. The repetitive ones get a one-click answer; the tricky ones still go to a human.
Hours back every week and faster replies — with the team's attention saved for the messages that actually need judgment.
For each workflow, the Study gives you what you need to decide with eyes open: the tool stack with real pricing, the build and run cost, an ROI you can sanity-check, and a clear verdict — build now, not yet, or skip.
Some workflows will not make the cut, and we will tell you which. The point is not to AI-everything; it is to find the one worth building first — then build it properly, one at a time.
Somewhere in it are a few everyday jobs that eat time and lean on the same people. Let us find them, weigh each one honestly, and figure out which is worth building first.
A composite, illustrative example used to show the kind of work an AI Opportunity Study surfaces. Figures shown are illustrative; a real Study uses your business and your numbers.