The short answer
AI quoting helps industrial distributors answer requests for quote faster by automating the slowest steps: reading RFQs that arrive by email, PDF or spreadsheet, matching each line to the right part number, applying pricing and availability from the ERP, and drafting the quote for a rep to review. It works best on high-volume, repetitive quoting such as fasteners, MRO and electrical supplies.
Key takeaways
- Quote turnaround is often limited by lookup and typing, not by pricing decisions.
- Part number matching is the hardest and most valuable step to automate.
- AI drafts the quote. Reps stay in charge of pricing judgment and customer relationships.
- Most distributors can automate quoting on top of the ERP they already run.
- Start with one high-volume RFQ type and measure turnaround before and after.
For most distributors, the quote is where the sale starts. A customer emails a list of parts, sometimes as a spreadsheet, sometimes as a scanned PDF, sometimes as a paragraph of text, and the first distributor to come back with a complete, accurate price often gets the order.
The volume is enormous. U.S. merchant wholesalers recorded $817.5 billion in sales in August 2026, according to the U.S. Census Bureau. A large share of that business runs through quotes that inside sales teams still build by hand, line by line.
Why is quoting such a bottleneck for distributors?
Because every RFQ arrives in a different format and every line needs a lookup. The pricing decision is often quick. Getting to it is slow.
- Messy intake. Requests come as emails, PDFs, spreadsheets, photos and drawings with a bill of materials, each laid out differently.
- Part number matching. Customers use their own part numbers, manufacturer numbers or plain descriptions, and reps translate each one to your SKU.
- Pricing rules. Contract pricing, customer tiers, quantity breaks and cost changes all have to be applied correctly.
- Availability checks. Stock, lead times and alternates live in the ERP or with a supplier.
- Retyping. The final quote is keyed into the ERP or a template, then sent and tracked separately.
When quotes take a day or more, the fastest competitor often wins regardless of price, and reps spend their time typing instead of selling.
What does AI quoting actually automate?
AI quoting automates the steps between receiving the request and a rep approving the price. Here is how the work typically splits.
| Step | What AI and automation do | What the rep does |
|---|---|---|
| Intake | Reads the email and attachments, identifies the customer and pulls out each line item and quantity | Nothing, unless the request is unclear |
| Part matching | Matches customer, manufacturer and descriptive part references to your SKUs and suggests alternates | Confirms low-confidence matches |
| Pricing | Applies contract pricing, tiers, quantity breaks and margin rules from the ERP | Adjusts strategic or competitive pricing |
| Availability | Checks stock and lead times and flags lines that need sourcing | Handles special orders and supplier calls |
| Draft and send | Builds the quote in the ERP or template and prepares the reply | Reviews, approves and sends |
| Follow-up | Tracks open quotes and reminds reps when to follow up | Has the customer conversation |
This kind of document reading and workflow automation is the core of our AI and intelligent automation work.
Why is fastener quoting a good fit for AI?
Fasteners combine huge catalogs with highly specific requests. One line can hinge on diameter, length, thread, grade, material and finish, and customers describe the same part many different ways. That makes matching slow for people and well suited to software that learns from your past quotes.
The same pattern applies to MRO, electrical, plumbing and industrial supplies: many small lines, many ways to describe each one, and a premium on speed. The more repetitive the request, the more of the quote AI can draft.
Want to see how much of your quoting could be drafted automatically? Book a working session and bring a handful of recent RFQs.
Should you buy quoting software or build on your ERP?
It depends on how standard your quoting is and how much of your advantage lives in pricing and matching rules.
| Approach | Fits when | Watch for |
|---|---|---|
| Off-the-shelf quoting tool | Quoting is fairly standard and the tool connects to your ERP | Limits on custom pricing rules and part matching logic |
| Custom automation on your ERP | Your pricing, matching or customer rules are a competitive advantage | Needs clear ownership and ongoing upkeep |
| Hybrid | A tool handles intake and drafting, custom logic handles matching and pricing | Integration between the pieces |
Either way, the connection to the ERP is what makes quoting accurate, and that is custom software and integration work.
How do you start an AI quoting pilot?
- Pick one RFQ type. Choose a high-volume, repetitive category, such as a product line or a group of regular customers.
- Collect history. Gather a few hundred past RFQs and the quotes you sent for them. They teach the matching and serve as a test set.
- Measure the baseline. Record turnaround time, quotes per rep and win rate today.
- Build with review. Have AI draft quotes while reps review every one at first, correcting matches so accuracy improves.
- Measure again. Compare turnaround, volume and win rate, then decide what to expand.
Our process follows the same shape: one problem, a measured baseline and a first fix before anything scales.
What else can distributors automate?
Quoting is usually the starting point, but the same tools apply across distributor workflow automation.
- Order entry. Reading customer purchase orders and creating sales orders automatically.
- Supplier invoices. Matching invoices to purchase orders and receipts and flagging price differences.
- Customer updates. Sending backorder, shipping and lead time notices without manual emails.
- Margin visibility. Seeing which products and customers actually make money, covered in building a margin by product and customer report and our data and BI work.
Mapping where orders and quotes stall before automating is business performance and operations work, and turning faster quotes into more wins is part of growth strategy for manufacturers and distributors. See more on our manufacturing, distribution and logistics page.
Frequently asked questions
What is AI quoting for distributors?
AI quoting uses software to read incoming requests for quote from email, PDFs and spreadsheets, match each line to your part numbers, apply pricing and availability from your ERP and draft a quote for a salesperson to review. It removes most of the manual lookup and typing that slows quote turnaround.
Can AI match customer part numbers to our catalog?
Yes, and it is usually the most valuable step. AI can learn from your past quotes and cross-reference tables to match customer, manufacturer and competitor part numbers, along with plain-language descriptions, to your SKUs. Low-confidence matches are flagged for a person instead of guessed.
Does AI quoting replace inside sales reps?
No. It removes the repetitive lookup and data entry so reps spend their time on pricing judgment, customer relationships and complex requests. Most distributors use the time saved to respond faster and quote more opportunities with the same team.
Do we need a new ERP to automate quoting?
Usually not. AI quoting can read pricing, inventory and customer data from the ERP you already run and create quotes in it through an integration or import. Replacing the ERP is rarely the first step, though clean item and pricing data makes automation much more accurate.
How do you measure whether AI quoting is working?
Track quote turnaround time, quotes handled per rep, match accuracy and win rate before and after the pilot. Turnaround and volume usually improve first. Win rate takes longer to read because it depends on pricing and competition, but faster responses tend to help.
