Collecting payments from business customers is one of the most time-consuming parts of finance operations. As companies scale, the number of invoices, customers, and inbound queries grows exponentially while the size of the accounts receivable (AR) team often stays the same.
Manual chasing, shared inboxes, and spreadsheets can work for a few dozen accounts, but not for thousands. To keep cash flowing and Days Sales Outstanding (DSO) under control, finance teams need automation that's smart, contextual, and customer-friendly.
Here's how to successfully automate B2B collections.
1. Centralise your collections workflow
The first step is to unify everything in one place. Many teams still manage invoices and follow-ups across email inboxes, spreadsheets, and ERP notes. A centralised AR system integrated with your ERP and CRM ensures every invoice, reminder, and customer message is visible in one workflow.
With a unified dashboard, teams can see who owes what, which customers have promised to pay, and where issues are stuck. This foundation is essential before introducing advanced automation.
2. Automate routine communication
Most overdue payments don't require complex negotiation — they just need a polite nudge. Automation can handle the repetitive 80% of reminders, freeing your AR specialists for higher-value cases.
AI agents can send contextual follow-ups, continue existing email threads, and adjust tone based on payment history. Instead of generic templates, each message feels human and relevant. The result is faster responses and fewer ignored reminders.
3. Track promise-to-pay commitments
A hallmark of effective automation is keeping track of what customers say. If a customer promises to pay next week, the system should automatically record that date, pause reminders until then, and resume follow-up only if payment hasn't arrived.
AI agents can extract promise-to-pay data directly from conversations, creating a live, self-updating view of expected cash inflow — improving both forecasting and customer experience.
4. Escalate intelligently at the customer level
Not every overdue invoice deserves escalation. Escalating on an invoice basis can lead to awkward scenarios — like sending a harsh reminder over a €150 invoice while the customer has paid everything else.
Automation should evaluate the customer's total exposure, factoring in the number of overdue invoices, total balance, and payment behaviour. AI-driven systems can automatically calculate when escalation is appropriate, ensuring consistent and proportional responses.
5. Resolve issues early
A significant share of overdue invoices stem from preventable issues: missing purchase order numbers, incorrect billing details, or pending approvals in the customer's AP portal.
AI agents can automatically detect and respond to these queries — sending invoice copies, verifying POs, or escalating discrepancies to the right contact — before they delay payment. Early resolution keeps invoices from aging and reduces the need for costly collection efforts later.
6. Involve sales and account management
B2B collections are relationship-driven. Involving customer-facing teams early helps maintain goodwill while getting results. AI agents can automatically flag high-value accounts that require human attention, notifying sales or account managers when payments are at risk or communication stalls.
This collaboration helps finance preserve relationships while keeping cash flow steady.
7. Measure and optimise continuously
Automation is not "set it and forget it." Track key metrics — DSO, promise-to-pay reliability, collection rate, and escalation rate — to refine your workflow. AI systems can analyse patterns and recommend changes, such as adjusting cadence or tone for certain customer segments.
The role of AI agents in B2B collections
Traditional automation tools handle rule-based reminders. AI agents take it further by understanding context, managing two-way conversations, and learning from interactions. They can:
Reply to common invoice queries automatically
Capture and track promise-to-pay commitments
Find the right contact when emails bounce
Escalate intelligently based on total exposure
Involve humans when nuance or negotiation is needed
By combining conversational AI with finance data, companies can collect faster, lower their DSO, and scale AR operations without growing headcount.
Conclusion
Automating B2B collections isn't just about sending reminders faster — it's about creating intelligent, context-aware workflows that mirror what great collectors already do. AI agents now make that possible: they handle routine outreach, track commitments, resolve issues early, and keep humans focused on exceptions.
The result is improved cash flow, happier customers, and a finance team that finally scales with the business.