Spend any time in your customer service department, and you are sure to see an entire team dedicated to entering customer orders and supplier updates. Most companies are still receiving orders by email.

Behind the scenes, your teams are:

• Reading POs and change requests from inboxes

• Manually interpreting PDFs and spreadsheets

• Re-entering data into IFS

• Manually notifying manufacturing, shipping, and procurement when anything changes.

Manual processes are eating into your ROI with increased HR costs, data entry errors, and processing miscues.

With the introduction of  25R2 IFS is introducing two digital agents to help alleviate order processing issues:

Customer Order Manager

Customer Order Manager is a digital agent that monitors order inboxes and automates the entry and validation of customer orders. Human agents no longer have to manually read emails, open and process PDFs, or Excel spreadsheets. Instead, the Customer Order Manager reads and interprets Customer Orders directly from an inbox, ensuring they are created accurately in the order management system. When an update to an existing customer order is received, the Customer Order Manager automatically updates the customer order and notifies the coordinator via Teams or Slack.

Don’t Lose Your Human Element!

The human agent only needs to monitor and approve the results of the Customer Order Manager. This reduces the time humans need to spend on mundane tasks such as data entry and inter-department notifications, freeing them up to do more customer relationship fostering and customer service that require more human interaction.

 

Supplier Order Manager

The Supplier Order Manager digital agent receives supplier confirmations and updates and applies updates to purchase orders before they become a problem in the supply chain. The digital agent also receives supplier invoices and applies them to existing purchase orders, ensuring every accounts payable entry is tied to a cost element.

For leadership teams, the value is clear:

• Faster order-to-cash cycles

• Reduced manual cost per order

• Fewer errors and downstream surprises

• Better scalability without linear headcount growth

This is not AI for experimentation, it’s AI applied to core financial and operational processes.

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