In a lot of distributors' offices, there is someone whose day is mostly typing. Orders arrive as emails, PDF purchase orders, spreadsheets, photos of handwritten lists and the occasional voicemail. Each one gets read, checked against the price list and keyed into the ERP, one line at a time.
It is careful, important work. It is also exactly the kind of work AI has become good at.
What AI order entry actually does
An order-entry agent does the same steps your team does, just faster:
- Reads the incoming order, whatever format it arrives in
- Pulls out the customer, items, quantities, PO number and delivery details
- Matches them against your customer list, item codes and price lists
- Drafts the order in your ERP or accounting system
- Flags anything it is not sure about, like an unknown part number or a price that does not match
The draft then goes to a person to review and release. On the clean orders, that review takes seconds. On the messy ones, the agent has already done most of the legwork and pointed at the problem.
Where it works well
AI order entry is a strong fit when:
- A good share of orders arrive by email or as documents rather than through a portal or EDI
- Customers use their own descriptions or part numbers, not yours
- The same customers order regularly, so there is history to learn from
- Your team spends a meaningful part of the day keying orders
Where it struggles
Be wary if:
- Your item master is messy, with duplicates or old codes, because the agent will match against bad data
- Pricing is mostly negotiated per order, rather than coming from a price list
- Orders are rare and very complex, like one large custom project a month
In those cases, the better first step is usually tidying the data or connecting the systems, not adding AI on top.
Start with one inbox
The best way to try it is narrow. Pick one order inbox or one group of customers. Run the agent in draft mode, alongside your team, for a few weeks. Compare what it drafts with what your team enters. Fix the mapping where it gets things wrong.
You will learn quickly where it is reliable and where it needs a person. Then widen it.
Keep your team in charge
The goal is not to remove the people who know your customers. They are the ones who catch the order that looks fine but is wrong, because they know this customer always means the other size. The goal is to stop them retyping, so they can spend their time on those judgment calls and on customers.
It is not just orders
Once order entry works, the same approach applies to other paperwork that arrives in your inbox: supplier order confirmations, packing slips, invoices, return requests. Each one is a document that gets read and keyed somewhere.
Built on your systems, not beside them
There are now plenty of AI order-entry products aimed at distributors. Some are very good. The question to ask any of them is how they connect to your ERP and your CRM, and who owns the setup when something changes.
That is where we come in. We build the agent around the systems you already run, whether that is SAP Business One, QuickBooks, Shopify or something else, so orders land where they need to without a new system in the middle.
Planning work like this? Part of it may qualify for Canada's SR&ED tax credits. Here is how SR&ED applies to custom development.