How to use AI to follow up on overdue invoices
Short answer
Export your AR aging report, ask an assistant for a chase list sorted oldest and largest first with disputed invoices held apart, and have it draft a reminder for each customer in the right tone. Check every amount and date against the aging before anything goes out. Collections tools such as Upflow, Chaser and Xero's JAX automate parts of this.
How to run AR follow-up with AI
- 1Export the AR aging report as CSV, with customer, invoice number, invoice date, due date, amount and any dispute notes.
- 2Ask for a chase list that skips invoices not yet due, holds disputed invoices in a separate list, and sorts the oldest bucket first, then the largest amount.
- 3Check that the chase list total plus the disputed and not-yet-due totals equals the aging report total.
- 4Ask for a reminder for each customer: friendly for the first nudge, firmer for the second, final for the last.
- 5Send the emails yourself, and log the date and any promise to pay against each invoice.
- 6Rerun the chase list every week from a fresh aging export.
Copyable prompt: weekly AR chase list
Upload this week's AR aging report as CSV, then paste this prompt.
Copyable prompt
I'm following up on overdue invoices for [business name, or "a small business"]. Today is [date]. I have uploaded aging.csv: customer, invoice number, invoice date, due date, amount due, notes. Please: 1. Build a chase list of invoices that are past due. Skip invoices that are not due yet. 2. Put any invoice whose notes mention a dispute, a credit or a query in a separate "on hold" table. 3. Sort the chase list by aging bucket (oldest first), then by amount (largest first). Show bucket subtotals. 4. Show three totals: chase list, on hold, not yet due. They should add up to the total of aging.csv. If they don't, tell me. 5. For each customer on the chase list, draft a short reminder email. Use a friendly tone for 1 to 30 days late, firm for 31 to 60, and final for over 60. Include the invoice numbers, amounts and due dates exactly as they appear in the file. Do not invent payment links, late fees or deadlines. I will review and send the emails myself.
Replace the [bracketed] placeholders. Remove client names, account numbers, and personal data before pasting into any AI tool.
How do you build a chase list with ChatGPT?
A free interactive lesson from Ynteractive walks through it: upload the AR aging CSV and ask for a chase list that skips invoices not yet due, keeps disputed invoices separate and sorts the oldest bucket first, then the largest amount[1]. In its test run, the chase list total looked short against the aging report only because the disputed invoice had been left out, which is why the lesson has you check the totals[1].
Which tools automate payment follow-ups?
Upflow's collection agents work on customer replies in its AR inbox, with Replies, Promise to pay and Disputes skills that admins set to Off, Suggestions only or Auto-mode; the agent does not reply when it isn't confident[2]. Chaser's AI assistant, powered by Google Gemini Flash, pulls overdue invoices into tables and builds reminder templates and chase schedules for you to approve[3]. Xero's July 2026 release announces JAX Payment Follow Ups, which will tailor collection plans to each customer's payment history[4].
Can AI predict which invoices will be paid late?
Business Central can. Microsoft documents a Late Payment Prediction extension that predicts whether posted sales invoices will be paid late, shows a confidence level for each prediction, and learns from invoice amounts, payment terms, credit memos and customer payment history[5]. On the cash side, Invoiced's CashMatch applies incoming payments to the right invoices and gives each match a confidence score[6], which keeps the aging accurate before you chase anyone.
Frequently asked questions
- What tone should an AI-drafted payment reminder use?
- Match it to how late the invoice is and how the customer has paid before. The Ynteractive lesson drafts friendly, firm and final versions[1], and Xero's announced Payment Follow Ups adapt the plan to each customer's payment history[4].
- Should I let AI send reminders automatically?
- Start with drafts. Upflow's Suggestions only mode sends nothing without a person seeing it first[2], and Chaser's assistant does not send emails without permission[3]. Switch on automatic sending only for routine first reminders, once the drafts have been reliable.
- What data does the assistant need?
- An AR aging report with customer, invoice number, dates, amount and dispute notes. Leave out bank details and anything else the reminder does not need.
Sources
- 1.Ynteractive: Collect overdue invoices with ChatGPT (interactive lesson)
- 2.Upflow docs: Collection agents
- 3.Chaser Help Center: Chaser's AI assistant
- 4.Xero media release: New AI innovations at Xerocon London (Jul 2026)
- 5.Microsoft Learn: Late Payment Prediction in Business Central
- 6.Invoiced: Cash application
Sources were checked when this page was last updated. Archived copies are cited where the original page could not be reached from our checker. Features and settings change, so confirm details with each vendor.
Not professional advice. This is general information, not accounting, tax, legal or financial advice. Check AI output yourself and consult a licensed professional for your situation. See our Terms of Use.
Related workflows
- Accounts Receivable
Build a Weekly AR Chase List and Reminder Drafts with AI
This free interactive lesson has a bookkeeper upload an AR aging report CSV to ChatGPT and ask for a chase list that skips invoices not yet due, holds disputed invoices in a separate list, and sorts oldest bucket first then largest amount. The user checks rows and totals against the file, then asks ChatGPT to draft friendly, firm or final reminder emails, verifies every fact, and sends the emails personally.
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Let an Upflow Collection Agent Draft Replies and Log Promises to Pay
Upflow's documentation describes AI collection agents that act on inbound customer emails in the Upflow AR inbox. Each agent has three skills, Replies, Promise to pay and Disputes, and admins set each skill to Off, Suggestions only or Auto-mode, then assign the agent to workflows. Replies must first be managed in Upflow, and the agent works only from customer, invoice and conversation data in Upflow.
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Rebuild Payment Chase Schedules with the Chaser AI Assistant
Chaser's help center explains that its AI assistant, powered by Google Gemini Flash, is a chat tool that can pull receivables data, such as top overdue invoices or highest-status debtors, into tables. It can also create new reminder templates, build chase schedules and assign customers to them, operating on a human-in-the-loop basis where users review and approve templates, schedules and contact moves before anything goes live.
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Predict Late-Paying Invoices with Business Central Late Payment Prediction
Microsoft Learn documents the Business Central Late Payment Prediction extension, which predicts whether posted sales invoices will be paid late so you can adjust payment terms or methods. Once enabled, a Payments Predicted to be Late tile opens Customer Ledger Entries with Late Payment and Prediction Confidence columns, and the model trains on invoice amounts, payment terms, credit memos and aggregated customer payment history.
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Tailor Payment Follow-Ups to Each Customer with Xero JAX
Xero's July 2026 media release from Xerocon London announces new features for JAX, its agentic AI platform. Under Payment Follow Ups, JAX will analyze a customer's payment history and execute tailored collection plans, such as consolidating invoices, timing nudges, or switching to SMS for non-responsive customers. The release also describes Bill Protection, which will inspect bills before payment for unusual amounts, altered bank details or unfamiliar suppliers.
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Apply Customer Payments to Invoices with Remittance Advice AI
Invoiced's cash application page describes a CashMatch AI algorithm that applies customer payments to the right accounts, invoices and balances, plus remittance advice AI where you upload a document and the system matches payments to invoices while flagging inconsistencies. It also mentions custom matching rules, a virtual lockbox for scanning paper checks, short-pay and over-pay handling, multi-invoice application and a confidence score from 1 to 100 percent per match.
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