In this article, we will explore what AI invoice processing is and how it can help your business. We also share our AI capture process for invoices. Read on to learn more.
Invoice processing using AI is the use of artificial intelligence to automate the extraction, interpretation, and management of invoice data. This technology leverages machine learning and natural language processing to efficiently handle large volumes of invoices which reduces human error and saves time.
Example: If a company buys "Dell Inspiron 15" laptops, the AI system reads the invoice, picks out important details like product name and number, and enters this information into the company's financial records without any human effort.
Use our 10 step process for invoice data extraction using AI. Simply follow the steps below.
Data extraction is the initial step where the AI system reads and extracts relevant data from the invoice, such as invoice number, date, total amount, and line items. This process uses Optical Character Recognition (OCR) to convert text from scanned invoices into machine-readable data.
Example: The AI extracts the invoice number "INV-12345", the date "2023-07-01", and a total amount of "$500.00" from an invoice for "50 units of USB flash drive at $10.00 each".
After extraction, the data is structured into a predefined format, such as JSON or XML, to ensure consistency and ease of further processing. This step involves mapping extracted data to the appropriate fields in the target structure.
Example: The extracted data is structured into JSON format: `{"invoice_number": "INV-12345", "date": "2023-07-01", "total_amount": "500.00", "line_items": [{"product": "USB flash drive", "quantity": "50", "unit_price": "10.00"}]}`.
The AI system validates the extracted data to ensure its accuracy and completeness. This includes checking for missing fields, verifying data formats, and cross-referencing with existing records.
Example: The system verifies that the invoice number "INV-12345" matches the expected format, the date is valid, and the total amount of "$500.00" corresponds to "50 units of USB flash drive at $10.00 each".
In this step, additional information is added to the extracted data from external sources or internal databases to enhance its value. This could include adding supplier details or matching product codes with descriptions.
Example: The AI enriches the invoice data by adding the supplier name "Quintana Co." and the product description "USB Flash Drive 16GB" for "USB flash drive".
The structured and validated data is integrated into the organization's ERP or accounting system. This ensures that all relevant departments have access to the most recent and accurate data.
Example: The invoice data is uploaded to the ERP system, updating the accounts payable module with the new entry for "INV-12345" from "Quintana Co." with a total amount of "$500.00".
Any discrepancies or errors identified during validation or integration are flagged for human review. This step ensures that anomalies are addressed before finalizing the data entry.
Example: The system flags an error if the total amount extracted does not match the sum of line items, prompting a human reviewer to verify the invoice details for "INV-12345".
Once processed, the invoice data is archived for future reference and compliance purposes. This involves storing the structured data in a secure, easily retrievable format.
Example: The structured data for "INV-12345" is stored in a secure archive, allowing for easy retrieval in case of an audit or future reference.
The captured invoice data is used to generate reports and perform analytics, providing insights into spending patterns, supplier performance, and cash flow management.
Example: Monthly reports are generated showing total expenditures, highlighting that "Quintana Co." accounted for "$500.00" of the month's spending on "USB flash drive".
Feedback from exception handling and reporting is used to refine and improve the AI system's accuracy and efficiency. This step ensures the system becomes more robust over time.
Example: Feedback from repeated errors with a specific supplier's invoices is used to adjust the OCR settings, improving future data capture accuracy for "Quintana Co.".
The AI system maintains a detailed audit trail of all actions taken during the invoice processing to ensure compliance with regulatory requirements and facilitate audits.
Example: The system logs every step taken for "INV-12345", including data extraction, validation, enrichment, integration, and exception handling, ensuring a complete audit trail.
Columbus Inc. is implementing an AI-based system to streamline their invoice processing. Here's how they implemented our process using a sample invoice from supplier "ElectroGoods Ltd."
The AI uses Optical Character Recognition (OCR) to extract key details like invoice number, date, total amount, and line items. For an invoice from "ElectroGoods Ltd.", it extracts invoice number "TG-7890", date "2024-05-15", and total amount "$1500.00" for "100 units of wireless mouse at $15.00 each".
Extracted data is structured into a predefined format like JSON.
The data is structured as:
{"invoice_number": "TG-7890", "date": "2024-05-15", "total_amount": "1500.00", "line_items": [{"product": "wireless mouse", "quantity": "100", "unit_price": "15.00"}]}.
The AI validates the data for accuracy and completeness by checking formats and cross-referencing records. It verifies the invoice number "TG-7890", date, and total amount "$1500.00" for "100 units of wireless mouse at $15.00 each".
Additional information like supplier details or product descriptions is added. The AI enriches the data by adding supplier "ElectroGoods Ltd." and product description "Wireless Mouse Model X1".
Validated data is integrated into the ERP or accounting system. The data updates the accounts payable module with entry "TG-7890" from "ElectroGoods Ltd." for "$1500.00".
Discrepancies are flagged for human review. If the total amount doesn't match the sum of line items, a reviewer checks the invoice details for "TG-7890".
Processed data is securely archived for future reference and compliance. The data for "TG-7890" is stored securely for easy retrieval.
Captured data is used for reports and analytics on spending patterns and supplier performance. Monthly reports show "ElectroGoods Ltd." accounted for "$1500.00" on "wireless mouse".
Feedback from errors is used to improve the AI system. Repeated errors with a supplier adjust OCR settings for better accuracy with "ElectroGoods Ltd." invoices.
The AI maintains an audit trail of all actions for compliance and audits. It logs each step for "TG-7890", ensuring a complete audit trail.
Here are some of the most common ways AI invoice capture software helps businesses:
AI automates data extraction and processing which reduces manual entry and errors. This speeds up processing times and allows employees to focus on more valuable tasks.
Automating repetitive tasks reduces the need for extensive manpower which lowers operational costs. This is particularly beneficial for handling large volumes of invoices.
AI achieves high accuracy in data extraction, ensuring correct invoice details. This minimizes discrepancies and the need for rework.
Faster invoice processing expedites payment cycles which improves cash flow and supplier relationships. Prompt payments can also lead to discounts and better credit terms.
AI can handle increasing invoice volumes without adding to the accounting team's workload. This scalability supports business growth without administrative bottlenecks.
AI ensures invoices comply with regulations and internal policies, avoiding legal issues and maintaining standards.
We hope that you now have a better understanding of what AI processing is for invoices and how to implement our invoice process using AI. If you enjoyed this article, you might also like our article on invoice OCR processing and invoice data capture.