How are distributors using AI today?
Most distributors start with pricing, inventory and demand planning, customer service, and sales support. NAW's 2026 research found pricing was the top AI priority for 27% of distributors surveyed. For mid-market firms, the faster wins are usually operational: reading emailed orders into the ERP, answering parts and stock questions from one place, receiving supplier invoices, and drafting quotes. These cut hours of retyping and searching, and they are easier to measure than a pricing engine.
Can AI enter orders from emailed purchase orders into our ERP?
Yes. A well-built order entry tool reads purchase orders in any format, matches each line to your catalogue using your cross-references and customer part numbers, checks quantities and prices against your rules, and creates the sales order. Anything that fails a check goes to a person. Start with your highest-volume customers and formats.
Do we need to replace or clean up our ERP before using AI?
No. Most useful builds sit beside the ERP or DMS you already run. They read from it and write back only what passes its normal checks. You do need clean data for the workflow you start with, such as a reliable item master and clear pricing rules for order entry. Fix that, ship the first build, and improve the rest of your data as each new build needs it.
How can AI help equipment dealers with the technician shortage?
AI won't turn a wrench, but it can give technicians back hours they spend away from billable work. Turning a technician's notes into a clean work order, answering procedure and warranty questions with the source cited, and estimating repair hours from past jobs all reduce admin time. Canadian dealers are short about 1,263 technicians a year, so every hour returned to the shop floor matters.
Is Microsoft Copilot enough for a distributor?
Copilot is a good starting point for email, documents, meetings and spreadsheet work, especially when teams are trained on their own workflows. It doesn't read POs into your ERP, match part numbers or apply your pricing rules on its own. Those need a custom build connected to your systems. Most firms need both: Copilot habits for everyone, and a few targeted builds.
How do we keep customer pricing and data safe when using AI?
Run builds in your own Microsoft or Azure environment, own the code, and confirm your data is not used to train public models. Fix Copilot oversharing before widening access, because Copilot shows users anything they already have permission to open. Limit each tool to the data it needs, log its actions, and require a person to approve prices outside your rules and anything sent to an OEM.
How long before we see results from AI?
Copilot habits built around real workflows can show time savings within weeks. A custom build such as order entry typically takes a few months to design, connect to your ERP and roll out, and depends on how clean the data is for that workflow. Set a baseline in the first month, such as inbox-to-order time or quote turnaround, so you can show the change in numbers, not opinions.