Purchase order processing is a classic example of work that is essential but adds little value when done manually. AI-powered document processing combined with Dynamics 365 can transform this process, reducing manual effort by 80% or more while improving accuracy and speed.
The Purchase Order Challenge
Most organisations receive purchase orders in multiple formats: emails with attachments, PDFs, scanned documents, and occasionally structured data. Each order needs to be reviewed, validated, entered into the ERP system, and processed through to fulfilment.
Manual processing is time-consuming and error-prone. Staff spend hours re-keying information that already exists in documents. Errors create downstream problems with wrong products shipped, incorrect quantities, or billing disputes. Delays in processing affect customer satisfaction and cash flow.
How AI Document Processing Works
AI document processing uses machine learning models trained to understand document structure and extract relevant information. Unlike simple OCR that just converts images to text, AI document processing understands context and can handle variations in document layouts.
For purchase orders, the AI model learns to identify:
- Customer information (company name, address, contact details)
- Order details (PO number, date, payment terms)
- Line items (product codes, descriptions, quantities, prices)
- Shipping information (delivery address, requested dates)
- Special instructions or notes
Once trained, the model can process new documents automatically, extracting structured data that flows directly into Dynamics 365.
Integration with Dynamics 365
The real power comes from integration with Dynamics 365. Extracted data does not sit in a separate system waiting for manual transfer. It flows directly into sales orders, validated against master data and business rules.
Customer Matching
AI extracts customer information and matches it to existing Dynamics 365 accounts. Variations in company names, addresses, and contact details are handled intelligently rather than requiring exact matches.
Product Matching
Customer product codes are matched to your internal product catalogue. The system learns from past orders, so even when customers use their own product numbers, matching improves over time.
Validation
Business rules validate extracted data before order creation. Pricing is checked against agreements. Credit limits are verified. Inventory availability is confirmed. Issues are flagged for human review rather than creating problematic orders.
Order Creation
Valid orders are created automatically in Dynamics 365. All standard order processing then applies: confirmation generation, fulfilment workflows, invoicing integration.
The Technology Stack
Several Microsoft technologies work together for AI purchase order processing:
- AI Builder: Document processing models that extract structured data from purchase orders
- Power Automate: Workflow automation that orchestrates the end-to-end process
- Dynamics 365: Business application where orders are created and processed
- Dataverse: Data platform that stores extracted data and enables validation
Implementation Approach
Document Analysis
Start by analysing the purchase orders you receive. How many different formats exist? What information varies between formats? What are the most common sources? This analysis informs model training and process design.
Model Training
AI Builder requires sample documents to train extraction models. The more varied your documents, the more samples you need. Microsoft’s pre-built models provide a starting point that can be customised for your specific documents.
Integration Development
Power Automate flows connect document processing to Dynamics 365. This includes customer and product matching logic, validation rules, and exception handling. The complexity depends on your specific business requirements.
Exception Handling
Not every order will process automatically, especially initially. Design clear exception handling so staff can efficiently resolve issues. The system should learn from corrections to improve over time.
Pilot and Rollout
Start with a subset of orders, perhaps from specific customers or order types. Validate accuracy, tune the model, and refine processes before full rollout.
Measuring Success
Key metrics for AI purchase order processing include:
- Straight-through processing rate: Percentage of orders processed without human intervention
- Processing time: Time from order receipt to system entry
- Error rate: Errors in processed orders versus manual baseline
- Staff time saved: Hours no longer spent on manual data entry
- Customer satisfaction: Faster acknowledgment and fewer order errors
Getting Started
AI purchase order processing is achievable for mid-market businesses using Microsoft’s standard tools. The key is starting with clear understanding of your current process and realistic expectations for automation rates.
Contact us for an assessment of AI automation opportunities in your order processing.
