We are a 30-person wholesale distributor. Our operations coordinator spends three hours a day manually re-keying messy, inconsistent customer purchase orders from email attachments into our ERP. What is our first practical AI use case to automate this without a massive IT project?

Question

Tyler Smith · Accepted Answer

Your first move must target a highly repetitive process that drains capacity. Do not build a custom system. Instead, use a basic document-processing AI assistant to extract unstructured data from PDF purchase orders and format it into a clean CSV file that can be uploaded directly into your ERP.

To set this up, draft a simple Standard Operating Procedure that outlines exactly how a human reads these purchase orders. Identify the critical fields such as part numbers, quantities, shipping addresses, and pricing. Feed these rules into a standard AI tool like the OpenAI Assistants API or an off-the-shelf document parser.

Assign the ownership of this system to your operations coordinator's seat on the Accountability Chart. They do not get replaced; their job shifts from manual data entry to quality control. They simply review the output for anomalies before hitting upload. This keeps a human in the loop, ensuring data integrity while instantly reclaiming fifteen hours of weekly capacity.

By treating this as an operations-improvement project rather than a technology experiment, you establish a quick win. It proves to your leadership team that AI is a practical tool for driving efficiency, not a complex science experiment. This builds momentum to tackle larger operational bottlenecks in your next quarterly planning session.