What are the best practices for using AI agents in accounts payable?

Until recently, AP automation meant OCR scans, rule-based routing, and manual approvals. But the work never really left. The average invoice still takes over two hours to process¹—adding up to more than 20 billion business hours every year.

That time isn’t just a number—it’s time finance teams could have spent closing the books faster, improving cash flow visibility, or finding ways to reduce costs. Instead, much of it goes to chasing approvals, fixing errors, and reconciling payments.

This marks the shift from AP 1.0 (automation) to AP 2.0 (autonomy). To prepare for this next era, finance teams should follow proven best practices that unlock the full potential of agentic AI—and make it easier to take advantage of solutions like Ramp Bill Pay’s AP agents.

Here are some best practices for using AI agents in accounts payable.

Why AI agents are changing accounts payable

AI agents are built to handle the full AP process—from capturing invoices to making payments—with minimal input. They use machine learning and context from your systems to read any invoice format, match it to a PO, and route it for approval based on your internal rules. And they get smarter with every transaction.

Traditional AP automation usually stops when something changes. A new vendor format or small error can break the flow and send the task back to someone on your team. AI agents adapt. They recognize patterns, resolve exceptions, and improve over time without needing constant updates.

Ramp’s Agents for AP are built around this adaptive intelligence—using learned context from contracts, prior payments, and communications to handle your invoices end-to-end with 7x fewer clicks than legacy systems.²

12 best practices for using AI agents for AP

Here are the top best practices for using AI agents in accounts payable:

• Baseline your AP flow and spot the friction
• Standardize invoice intake for straight-through processing
• Automate invoice coding
• Set up high-confidence matching with clear tolerances
• Make approvals dynamic, not static
• Design exception playbooks that teach the agent
• Generate approval summaries to strengthen context and control
• Keep systems in sync to avoid reconciliation headaches
• Build in continuous risk controls and auditability
• Put humans in the loop where judgment is needed
• Strengthen fraud prevention with continuous AI monitoring
• Measure, review, and tune on a regular schedule

1. Baseline your AP flow and spot the friction

You can’t improve what you haven’t measured. Without a clear baseline, it’s hard to show progress, train AI on the right problems, or set realistic goals. A good baseline makes sure you’re not just automating busywork. It gives you something to measure against as your AI agent learns and improves.

Start by mapping out how a typical invoice moves through your process:

• Track time spent at each stage. Follow an invoice from intake to payment and record where delays happen.
• Document intake channels and approval paths. Note how invoices arrive (email, mail, or EDI) and how they’re approved by amount, type, or department.
• Mix data with team input. Look at exception counts, rework rates, and employee feedback to surface hidden pain points.
• Check error logs and vendor inquiries. Spot recurring issues like duplicate invoices, missing info, unclear thresholds, or manual re-entry.

This gives you a real baseline for measuring accuracy and processing speed. It also gives your AI agent a clear starting point and a way to track what’s getting better.

2. Standardize invoice intake for straight-through processing

AI is only as accurate as the invoices it receives. The more consistent your intake, the fewer exceptions show up, and the more invoices can process from start to finish with little human input.

Structured formats like XML and EDI work best because they include labeled fields the system can read easily. Structured PDFs with predictable layouts also perform well, as do API submissions using formats like JSON.

Intake methods matter just as much. Vendor portals enforce structured fields, while email-to-AP pipelines can auto-extract attachments. Modern OCR powered by machine learning also makes it possible to process less consistent invoices. It can read across different layouts, handle abbreviations and multiple languages, and even work with poor-quality scans. Over time, these systems get better as they learn from human corrections.

How invoices arrive matters too:

• Vendor portals help standardize input with required fields
• Email-based intake can work as long as your system can extract and read attachments
• Modern OCR (optical character recognition) powered by machine learning can now handle messy layouts, abbreviations, multiple languages, and even low-quality scans

When invoice intake is predictable, everything that comes after it gets easier. This includes approvals, matching, and payment.

3. Automate invoice coding

Manual GL coding is one of the most repetitive and error-prone parts of accounts payable. AI agents can remove that friction by automatically classifying invoices based on historical data, vendor patterns, and cost center rules.

To make automation effective and auditable:

• Train models on clean data: Use past invoices with verified coding as your baseline to help the agent recognize vendor and spend patterns.
• Set confidence thresholds: Allow high-confidence predictions to post automatically, while routing low-confidence cases to human review.
• Enforce clear overrides: Give reviewers an easy way to correct coding and feed those updates back into the system for continuous learning.
• Validate against policy: Ensure codes align with chart-of-accounts rules and budget categories to avoid downstream reconciliation issues.

Automated coding saves hours of manual work and builds a foundation for more reliable spend classification and real-time reporting accuracy.

4. Set up high-confidence matching with clear tolerances

Once invoices are standardized, the next step is matching them to purchase orders and receipts. This is where throughput gets gained or lost. Clear thresholds reduce false exceptions, let humans focus on real problems, and create a reliable audit trail.

Use your AI agent to automate two- or three-way matching and save human effort for true exceptions. Key practices include:

• Setting policy-based tolerances. Allow small price or quantity differences to auto-approve, while sending anything outside policy for review.
• Routing exceptions with context. Present the PO, receipt, and invoice side by side, with the difference highlighted and a suggested resolution.
• Building vendor-specific profiles. Teach the system to handle harmless, recurring quirks, such as rounding issues, while capping these rules to prevent drift.
• Logging every decision. Record the data used, the rule applied, and the outcome to make sure everything's transparent and auditable.

With these safeguards in place, matching becomes more reliable and less noisy, so your team can focus on the exceptions that actually need attention.

5. Make approvals dynamic, not static

Static approval chains slow things down and often turn into rubber-stamping. Dynamic routing keeps control in place by adjusting the level of review to the actual risk.

Set rules that trigger approval only when necessary. Use factors like invoice amount, cost center, vendor policy, spend category, or vendor risk score to guide routing. Low-value, low-risk invoices can auto-approve. Higher-value or higher-risk ones can go through additional checks.

When an invoice does need human review, give the approver everything they need up front like policy references, prior spend history, relevant contracts, and past communication. This helps them make faster, better decisions without extra back-and-forth.

6. Design exception playbooks that teach the agent

Every exception is a chance to make the system smarter. When you handle issues consistently, you not only speed up resolution but also give the AI the training data it needs to improve over time.

When an invoice falls outside your set tolerances, the agent should route it to the right person with full context. That includes highlighting the issue and attaching all supporting details, like PO lines, receipts, contracts, and past communications.

Routing should reflect the issue type. Price differences can go to Procurement, quantity mismatches to Receiving, and billing disputes to AP or the vendor owner.

To keep things moving, prioritize exceptions by urgency. Use criteria like discount windows, vendor risk, and invoice size to sort what matters most. Each of those decisions helps the AI adjust future suggestions, update vendor profiles, and refine its tolerances.

7. Generate approval summaries to strengthen context and control

AI agents can simplify approvals by generating clear, one-view summaries that highlight what approvers actually need to see, reducing back-and-forth and missed details.

Approval summaries should::

• Surface key context. Display total amount, vendor, coding, policy references, and any anomalies at the top of the summary
• Include risk signals. Highlight exceptions, duplicate checks, or new vendor changes so approvers can spot red flags fast
• Link supporting docs. Attach invoices, POs, receipts, and past approvals in one view to eliminate digging across systems
• Keep it lightweight. Focus on clarity and relevance; too much data defeats the purpose of automation

These summaries give reviewers confidence to approve faster by bringing transparency and accountability into every decision.

8. Keep systems in sync to avoid reconciliation headaches

When your ERP, AP, and payment tools aren’t aligned, it creates confusion. You get false exceptions, duplicated work, and AI suggestions that don’t match what’s actually happening. Keeping everything in sync builds trust in the data and the decisions your system makes.

Use built-in integrations when you can. They’re easier to maintain and usually require less custom setup. If that’s not possible, APIs or integration platforms can connect your systems—but make sure they all follow the same rules, with clearly mapped fields and a shared source of truth.

Decide which system owns each data type. That might be your ERP for vendors, your procurement tool for POs, and your AP system for invoice records. Map those fields once, document them, and use two-way sync with retry logic and conflict handling to keep everything aligned over time.

9. Build in continuous risk controls and auditability

AP is a common target for fraud because risky transactions can hide in day-to-day volume. Smart AI helps flag what humans might miss, and a strong audit trail keeps you ready for reviews or compliance checks.

• Spot anomalies before they become problems. Watch for red flags like duplicate invoices with slight edits, sudden vendor bank detail changes, transactions just under approval limits, or weekend submissions. Also look for volume spikes or invoice mismatches against contract terms.
• Take action before money moves. Pause suspicious invoices automatically, require a second check for bank updates, and escalate approvals when something doesn't add up.
• Make compliance automatic. Enforce separation of duties, track every action and system change, and align your process with the standards that apply to your business.
• Keep your review rhythm tight. Run quarterly checks on your configuration, review a sample of exceptions each month, and conduct regular access reviews with clear documentation.

AI can spot the risks, but humans still set the rules. Keep both in sync, and your controls will get stronger over time.

10. Put humans in the loop where judgment is needed

AI can take care of repetitive tasks, but decisions, relationships, and accountability still belong to people. Shifting your team’s focus to strategy and judgment improves accuracy and keeps them engaged and impactful.

Start by evolving roles:

• Move data-entry positions toward exception handling, vendor communication, and approvals
• Give AP specialists the time to spot trends and improve workflows
• Let managers focus on bigger-picture work like vendor relationships, payment timing, and cash strategy

Support these shifts with role-based training and clear communication. Make sure everyone understands not just what’s changing, but why it matters.

It also helps to align across functions. Create a shared governance structure that brings together AP, procurement, treasury, and IT. When everyone uses the same terms and knows their role, there’s less confusion and more accountability.

11. Strengthen fraud prevention with continuous AI monitoring

AI agents can monitor transaction behavior at scale. By layering anomaly detection on top of approval workflows, finance teams can catch subtle risks before they escalate.

• Spot anomalies in real time. Flag invoices just below approval limits, duplicate submissions with small edits, or sudden vendor bank changes.
• Pause and verify risky payments. Hold suspicious invoices automatically and trigger a second review before money moves.
• Secure sensitive actions. Require multi-factor authentication for vendor bank updates and policy exceptions.
• Log everything automatically. Track every change, decision, and exception in a searchable audit trail for internal or external reviews.

Continuous fraud detection keeps your controls sharp and helps your team trust the automation as your AP volume grows.

12. Measure, review, and tune on a regular schedule

Performance drifts without oversight. A small, stable set of metrics reviewed on a predictable cycle keeps improvements building up and ROI visible.

Set up a steady operating rhythm: review auto-approvals and long-tail exceptions weekly, tune thresholds and routing monthly, and recalibrate models and compliance quarterly.

And lastly, communicate progress clearly. Use dashboards to show trends and brief one-page summaries for executives. Always connect improvements to financial outcomes like cash flow gains, discount capture, and risk reduction.

What’s next for AI agents in AP?

Agentic AI is just getting started. The next wave of capabilities will go beyond processing speed and start helping finance teams make smarter decisions in real time.

• Smarter forecasting: Predictive models will flag potential cash flow gaps, vendor risks, or missed savings before they happen, giving you time to act.
• Conversational interfaces: Teams will be able to approve invoices or ask about vendor history using plain language instead of dropdowns and codes.
• Intelligent vendor insights: Systems will suggest when to pay, based on payment history, contract terms, and market data to balance vendor health with cash strategy.
• Better document understanding: Improved AI will handle messy invoices, handwritten notes, and nonstandard formats with less manual cleanup.

Ramp’s AP agents are built to evolve alongside this shift—continuously learning from new data, adapting to changing business processes, and integrating with emerging AI capabilities as they mature. As these technologies advance, Ramp Bill Pay continues to bridge AP automation with intelligent autonomy—helping finance teams work faster, reduce friction, and make smarter spend decisions across the entire finance stack.

Ramp's AI agents for accounts payable: How to turn AP's hardest tasks into touchless processes

Manual invoice coding, fraud risks, approval delays, and missed cashback opportunities are big operational challenges in accounts payable. Ramp has built specialized AI agents to tackle these specific problems, turning time-intensive manual workflows into automated processes that work on their own while keeping your financial controls in place.

Ramp Bill Pay is the first autonomous AP software system that processes invoices end-to-end without any manual work. Ramp's AI agents for AP include specialized systems for auto-coding, fraud prevention, approval management, and payment optimization. These agents work together to turn traditional manual processes into coordinated autonomous workflows.

Here's how they do it:

Auto-coding agent

Traditional AP requires accountants to manually code every invoice line item — searching through historical records, referencing old spreadsheets, or relying on tribal knowledge whenever vendor formats change.

Ramp’s auto-coding agent eliminates that work. It learns from your organization’s historical payment and accounting data to apply GL codes automatically, line by line. The agent reads invoice details such as product IDs, descriptions, and “Ship to” fields to map each expense to the correct GL code instantly.

If your team receives a multi-line utility bill across different locations, the agent allocates every charge to the right location-based code without a single manual touch.

Fraud prevention agent

Invoice fraud hurts. The mid-market average loss is $280,000 per incident.*

Ramp’s fraud-prevention agent stops risk before approval — not after payment. Trained on hundreds of thousands of invoices, the agent uses 60+ fraud signals to identify suspicious activity early.

It flags issues like unverified bank details, mismatched vendor domains, or edited invoice copies before they move forward. For transactions above $5,000 tied to new or unverified accounts, the system automatically pauses payment for human review.

Verified vendors in Ramp’s network bypass unnecessary checks, so legitimate payments move fast.

Approval agent

Approvals often stall when context is missing. Managers waste time hunting down contracts, prior bills, or pricing details just to make a decision.

Ramp’s approval agent fixes that. It summarizes everything approvers need — vendor history, contract terms, PO matches, prior invoices, and coding verification — all in one view. The agent even explains why each approver is in the workflow and highlights changes such as pricing differences or contract deviations.

Decision-makers can approve or reject in seconds instead of chasing context across multiple systems.

Agent for automatic card payments

Paying by ACH is fast—but often leaves money on the table.

Ramp’s payment-optimization agent finds card-eligible invoices automatically and completes card payments on your behalf. It inputs card details directly into vendor portals, eliminating manual entry, phone verifications, and copy-paste steps.

The agent consolidates payments across vendors for operational efficiency and identifies the best opportunities to earn cashback through strategic card usage.

Get touchless accounts payable with Ramp's AP agents

Ramp's AP agents work together within your existing workflow, connecting with your current ERP and accounting systems through pre-built connectors. You don't need to overhaul your entire AP process or retrain your team on complex new systems. The AI handles the heavy lifting while you keep control over approval hierarchies, coding rules, and payment preferences.

Finance teams using Ramp now process invoices with 7x fewer clicks than legacy systems like BILL, closing their books up to two days earlier and earning millions in cashback through optimized payments.³

Step away from your keyboard. The future of touchless accounts payable is here—with Ramp Bill Pay’s AP agents.

¹Accounts Payable Key Benchmarks, APQC.

²Business Leaders Beware: Three Common Invoice Scams, Forbes.

³Based on internal product testing performed in September 2025 evaluating the number of clicks used to process a typical invoice.