While AI and automation can dramatically streamline accounts receivable operations, they aren't a complete replacement for human oversight.

At Fazeshift, we provide finance and accounting teams with the powerful tools they need to automate tasks and processes. Still, we recognize certain decisions require deep knowledge and keen judgment that can only come from people on your team, not an AI agent.

Whether it's managing exceptions, handling payment negotiations, or protecting customer relationships, manual intervention remains a critical part of a well-balanced accounts receivable strategy.

‍

Key Takeaways:

• While AI can automate many accounts receivable processes, your team’s judgment is still essential in some complex, nuanced, or high-risk situations.
• AI enhances but doesn’t replace the real-life relationships that you’ve built with your customers. The contextual knowledge and rapport that your team has built with customers can’t be replicated by an automation platform.
• Some payment disputes, custom contracts, and unique customer scenarios still require manual review and authorization.
• Built-in checks and balances, such as manager sign-offs and multi-level reviews, can help your organization avoid costly missteps.
• Fazeshift ensures that finance and accounting teams have visibility into every decision made by task-driven AI agents through an auditable trail of actions and approvals for full accountability.

‍

Why there should be manual intervention in AR automation

‍

A lot of thought goes into how AI agents work and the edge cases they can solve, but there may be times when your team will want to do a final round of manual checks before certain actions are taken.

Fazeshift’s goal is to automate as much of your AR processes as possible, and while our AI agents are designed to do that, there are times when a person’s judgment is still needed to review exceptions, address unusual situations, and make difficult decisions.

Not every transaction or customer is the same, especially when you’re dealing with disputed charges, unusual payment terms, and unique contract conditions for a specific customer.

For example, Fazeshift’s AI agents are designed to handle contract reviews and payment disputes, but there may be times when it’s more appropriate for someone on your team to make a judgment call, handle negotiations, or review proposed actions, based on their background knowledge of a customer account.

Here are just a few examples that we’ve seen for accounts receivable teams:

• AI can flag high-risk behaviors for credit management purposes, but it may be prudent for someone on your team to review a customer’s creditworthiness, approve credit limit changes, or ultimately place a hold on an account.  
• Managerial review and sign off may be needed for custom agreements with certain terms or conditions to avoid financial mishaps and preserve customer relationships, such as a steep discount, an out clause, or another non-standard risky term.
• AI can find duplicate payments for an invoice during the automated cash application process and provide a recommendation, but a manager may still be needed to review and authorize next steps.
• Customers may ask for a payment plan in their response to an automated payment reminder or dunning letter. While AI can detect this request, a manager may still need to approve it.  

There are also times when manager- or executive-level approval will be needed for billing adjustments, large write-offs, and other situations that may have significant financial implications.

Your organization may also have policies and guidelines for very large or sensitive transactions, which may require manual approvals and multi-level reviews for specific types of customers or invoice amounts.

‍

‍

Leverage built-in workflow approvals

‍

There’s no doubt that AI is a great tool for automating accounts receivable processes up to a certain point.

AI agents may be intelligent and capable of learning from actions made by your team, but it simply can’t replace the relationships that your team has built with customers over time and all the contextual knowledge that goes along with it.

To ensure that specific people on your team can manually review, verify, and authorize — or otherwise override — automated actions, these types of controls should be built into any software solution that you use.  

At Fazeshift, we built transparency and accountability into our platform by enabling finance and accounting teams to see what data was used by an AI agent, how it was interpreted, how it came to a conclusion, and what actions it’s suggesting.

Fazeshift even has an auditable trail of all the actions an AI took and who may have had to step in and approve them along the way.

‍

Insist on robust automation controls for accounts receivable

‍

AI and the automation it offers are powerful tools for optimizing accounts receivable processes, but they work best in lockstep with your team’s insights and experience.

Fazeshift’s AI agents are designed to automate tasks that are often complex and nuanced, but we also recognize the importance of giving your team the ability to step in when it matters most or when the stakes are high.

‍Try Fazeshift and see how combining automation with clear approval workflows and transparency enables accounts receivable teams to move faster without sacrificing control or customer trust.