AI Agents for Accounts Receivable: Feature Checklist for Finance Teams in 2026

For years, accounts receivable automation meant one thing: replacing manual tasks with workflows.

That helped. But it didn’t solve the real problem.

Most finance teams still spend too much time on manual data entry, routine follow-ups, and chasing payment updates across multiple systems. Meanwhile, leadership wants better cash visibility, faster close cycles, and more reliable cash flow forecasting — even as invoice volume rises and customer payment behaviour becomes harder to predict.

In 2026, the shift is clear. AR isn’t just a back-office process anymore. It’s a cash flow function. And finance operations teams are starting to adopt AI-powered agents that can do more than automate steps — they can manage workflows end-to-end, based on your policies and rules, while keeping people in control.

So what should you actually look for when buying accounts receivable software with AI agents? This article breaks down the key features to look for — so your finance stack supports business strategy and business growth, not just collections admin.

What are AI agents for accounts receivable?

AI agents for accounts receivable are AI-powered systems that don’t just support your AR team — they actively run parts of the process. Instead of surfacing insights and leaving your team to do the work, an agent can plan actions, trigger workflows, and execute routine tasks across collections, cash application, and customer follow-ups. Think: a digital collections operator that understands what’s due, who’s at risk, what the next step should be, and when to escalate — without someone manually pushing every button.

Done well, they take on repetitive tasks that sit between collections, cash application, and day-to-day accounting tasks. This reduces data entry errors and freeing finance teams to focus on higher-value work.

The key difference vs rules-based workflow automation is flexibility. Traditional automation follows fixed “if this, then that” rules and still breaks when reality gets messy (partial payments, disputes, changing payment behaviour, missing remittance info). That’s why AI agents matter: they’re better suited to exceptions that break invoice automation and slow progress towards eliminating manual data entry.

However, while AI agents can adapt using signals, patterns, and context, they still need human oversight. That means finance teams stay in control through approvals, audit trails, and clear policies, while the agent handles the repetitive execution. Kolleno’s AI Agent is positioned exactly this way: you can assign AI Agents to automate collections and reconciliation processes through “Agentic Workflows.”

AI agents vs traditional AR automation software

On paper, most accounts receivable software sounds similar — especially once every vendor starts describing their AI tools as “AI-powered”. But the best accounts receivable software doesn’t just automate steps. It executes workflows reliably across edge cases.

There’s a huge gap between tools that automate steps and tools that can run the workflow. That’s what makes AI agents different — they don’t just help finance teams work faster. They help finance teams do less manual work altogether, while keeping control through human oversight and audit-ready governance.

Feature checklist: what finance leaders should demand in 2026

Most accounts receivable automation software looks good in a sales deck. The difference shows up in the detail — the specific features that remove manual steps, reduce mistakes, and keep collections moving without constant intervention.

Here’s the practical checklist to use when comparing AR collections software and AI agents in 2026:

Accounting/ERP integrations

Direct integration with your ERP system / accounting systems (e.g., NetSuite, Xero, QuickBooks Online), with two-way sync of invoices, payments, credit notes, and customer records.

Automated invoice reminders

Automated reminder sending based on invoice status (upcoming due, due today, overdue), including configurable timing and escalation.

Configurable dunning sequences

Multi-step dunning workflows that change based on how overdue an invoice is (and can stop automatically once paid).

Collections task assignment

Automatic task routing to the right person (by customer, region, portfolio, invoice value, or collector workload).

Centralised customer communications log

A full message history per account, including emails, call notes, promises to pay, and dispute notes.

Email templates with invoice-level variables

Templates that automatically merge invoice and customer details (invoice number, due date, amount due, payment link, etc.).

Dispute management

Ability to log disputes, assign owners, track status, pause collections, and keep a complete record for audit preparation.

Payment links inside reminders

Built-in payment links in chase emails that make it easy for customers to pay immediately.

Partial payment handling

Support for part-payments without breaking the workflow or forcing manual reconciliation workarounds.

Cash application / automatic payment matching

Cash application features that match payments to invoices (including incomplete remittance data) and reduce manual entry.

Short payment and deduction tracking

Ability to flag short payments automatically, track reasons, and keep the invoice status accurate.

Collector dashboard

A single collections workspace showing what needs action today (prioritised lists, ageing, tasks, and next steps).

Audit trail

Full audit trail showing what was sent, when it was sent, who triggered it, and what changed across the account history.

Role-based permissions

Granular access control across finance teams (e.g., collectors vs finance leaders vs admins) to ensure human oversight and governance.

How Kolleno’s AI Agent fits into the 2026 AR feature checklist

Kolleno’s AI Agent is built specifically for accounts receivable work — not generic “AI for finance”. Kolleno positions it as a way to assign AI Agents to automate collections and reconciliation processes using Agentic Workflows, so the system can execute AR actions rather than just surface recommendations.

Practically, that means the AI Agent can help collections teams with the day-to-day mechanics of chasing: building workflows that adapt based on customer context, sending personalised messages using invoice and contact information, and recommending next best actions through an “AI Copilot” layer. It’s designed as a collections assistant — the kind that reduces time spent working out who to chase, when to chase, and what to say.

Kolleno also links its agent approach to a major AR bottleneck: cash application and reconciliation. In its AR automation content, Kolleno describes connecting to bank feeds and using AI-driven reconciliation to match incoming payments to invoices, then syncing payment status back into the accounting system. That matters because cash application is where many finance teams still get dragged back into manual processes.

Finally, Kolleno frames its AI capabilities around better decision-making as well as execution — including predicting payment likelihood, detecting at-risk accounts, dynamic credit scoring, and prioritisation. That’s the direction AR collections software is heading in 2026: not just “send reminders faster”, but use predictive analytics to focus effort where it moves cash flow most.

Final thoughts

In 2026, the AR tools that win won’t be the ones with the flashiest “AI-powered” claims. They’ll be the ones that actually remove manual effort from collections, cash application, and customer follow-ups — while giving finance leaders the controls, audit trail, and human oversight they need to stay confident in the numbers.If you’re reviewing accounts receivable automation software this year, use the checklist in this guide and prioritise tools that can execute workflows end-to-end, not just generate reminders. To see what that looks like in practice, book a demo of Kolleno and explore how its AI Agent can help your team collect faster and improve cash flow visibility.