How to Organize a Quotation Inbox With AI

Quotation requests arrive with different formats, incomplete information and changing deadlines. The first useful role for an AI agent is to make that flow visible: identify the request, capture the facts and route it to the right owner.

Define a common request record

List the fields a team needs to prepare a response: customer, requested service, locations, dates, volumes, attachments and deadline. Capture a source link to the original message. If a field is missing or uncertain, mark it for follow-up rather than filling it by guesswork.

Keep routing rules explicit

A workflow can classify new requests, attach documents, create a task and notify the responsible team. Rules should cover duplicates, existing customer accounts, urgent deadlines and out-of-scope enquiries. Make ownership and escalation visible to everyone who uses the inbox.

Protect the quote itself

Initial triage is different from calculating a price. Pricing depends on current rates, capacity, commercial terms and approval rules. Treat automatic quote generation as a later phase that requires verified data and a clear human approval step.

Test the pilot against real work

• How many eligible requests are captured correctly?
• How often does the agent flag missing or conflicting information?
• How long does assignment take before and after the pilot?
• Are any requests missed, duplicated or sent to the wrong owner?

Measure those outcomes over a representative set of inbox messages. A pilot is successful when the team trusts the queue and spends less time chasing context, not when an attractive demo looks fast.