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AI-based invoice processing or automated invoice processing is no longer a sci-fi dream but a present reality. It is reshaping the way businesses manage their accounts payable (AP).

PwC's Global Artificial Intelligence Study expects the potential contribution of AI to the global economy by 2030 to be close to $15.7 trillion. The rapid evolution of artificial intelligence (AI) and machine learning (ML) is pushing the boundaries of what's possible in business automation.

From automating data extraction to identifying invoice discrepancies, AI-based invoice processing is making accounting and spend management operations smoother, faster, and more reliable. So, what exactly is AI-based invoice processing, and how does it work?

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What is AI-based invoice processing?

AI-based invoice processing, also known as AI for invoice processing, uses machine learning (ML), optical character recognition (OCR), natural language processing (NLP), and workflow automation to automate the extraction, validation, and processing of invoice data and route it through the appropriate channels and tools for approval and payment.

Here's a quick glimpse into how AI and OCR combine to extract invoice data
Here's a quick glimpse into how AI and OCR work together to extract invoice data

AI invoice processing leverages several key technologies to automate and streamline the accounts payable workflow:

Machine Learning: ML algorithms learn from historical invoice data to identify patterns, extract relevant information, and make accurate predictions, reducing manual intervention. Machine learning invoice processing enables continuous improvement and adaptation to diverse invoice structures.

Natural Language Processing: NLP allows the AI system to recognize and interpret human language on invoices, extracting critical information like vendor names, invoice numbers, and payment terms, even from unstructured or differently formatted data, making invoice processing more efficient and accurate.

Optical Character Recognition: OCR technology converts text on invoice images into machine-readable text, capturing and digitizing paper invoices or converting scanned invoices into editable formats. It enables AI invoice data capture–accurate extraction of necessary information ready for processing and workflow automation.

Workflow automation: Workflow automation integrates these technologies, creating a seamless end-to-end process. It routes invoices, triggers notifications for approvals, and integrates with existing accounting systems, eliminating manual handoffs and ensuring a smooth flow of information.

Traditional invoice processing workflow often involves data entry, approval-chasing, and manual reconciliation, which can be time-consuming and error-prone. AI-based invoice processing automates these tasks, reducing the need for manual intervention. It can handle various invoice formats, including scanned images and PDFs, and auto-fill and validate entries. AI invoice recognition enables these systems to accurately identify and extract relevant information from invoices, regardless of their format or layout.

How does AI-based invoice processing work?

Did you know that AI and automation-based invoice processing can reduce average costs from $40.70 to $3.34 and the turnaround time from 16.3 days to 3.8 days? Let's break down how it achieves such efficiency:

AI Invoice Processing ROI Calculator

AI invoice processing ROI calculator

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1. Invoice capture: The AI solution scans the physical or digital invoices. All you have to do is upload the invoice, and the software automatically converts the data into machine-readable format.

2. Data extraction: Once the invoice data is captured, the AI uses ML and NLP to extract relevant information such as invoice number, vendor details, date, total amount, line item details, etc.

3. Data validation: Post extraction, the AI validates the data by matching it with the purchase order details in the system. This step ensures that there is no discrepancy between the invoice and the order details.

4. Manual intervention and error correction: If the AI detects any discrepancy that it cannot resolve, it flags the invoice for manual review. Manual modifications help the AI learn and improve its accuracy in the future.

5. Route for approval: After data validation and error correction, the software routes the invoice to the relevant person or team for approval. This step helps in maintaining control and transparency in the process.

6. Payment processing: Once approved, the solution forwards it for netting or payments based on the invoice terms and business rules, helping avoid late fees and maintaining good relationships with vendors.

Struggling with high invoice volumes?

Struggling with high invoice volumes?

Get best-in-class OCR, customizable workflows, and integrations with QuickBooks, Xero, SAP, and Zapier to manage larger invoice volumes without additional resources.

How does incorporating AI solve common challenges in invoice processing?

Invoice processing may be a time-honored business practice, but it's not without its challenges. Whether you're a small enterprise or a large corporation, inefficiencies can creep in, leading to financial loss and wasted resources.

Problems like delayed orders due to late supplier payments, credit denial from past inconsistencies, and time wasted fixing errors and chasing approvals are all too common.

Thankfully, the recent incorporation of AI into invoice processing has helped businesses mitigate many of these issues.

An overview of how AI overcomes invoice processing hurdles, enhancing efficiency and accuracy.

Problem Solution Benefit
Manual Data Entry is slow and error-prone AI utilizes OCR to instantly capture and digitize data, while ML refines data extraction. Reduces processing time and human error, increasing overall productivity.
Inconsistent data entry leads to payment errors AI cross-verifies data against existing records, instantly correcting inconsistencies. Enhances payment accuracy and vendor trust, reducing costly reconciliations.
Approval bottlenecks delay supplier payments AI automates approval workflows, alerting approvers with smart notifications. Streamlines payment timelines, ensuring a smoother supply chain operation.
Tracking paper invoices invites fraud and loss AI creates a digital trail for every transaction, securely archiving invoices. Bolsters security and compliance, enabling easy retrieval for audits.
Complex invoices require extensive manual review AI learns to interpret various invoice formats, accommodating unique details. Adapts to multinational formats, simplifying global transaction management.
Growing businesses struggle to keep up with invoice volume AI scales dynamically with business needs, processing more data without added staff. Supports business expansion without the drawbacks of increased manual labor.
Uncertain cash flow complicates financial planning AI provides predictive analysis for upcoming payments and receivables. Offers actionable financial insights, leading to smarter cash management.
Different software systems do not communicate efficiently AI ensures seamless integration, transferring data automatically between systems. Connects disparate software, creating a cohesive financial ecosystem.
Start eliminating manual data entry today

Start eliminating manual data entry today!

Automate invoice data capture, validation, and processing with Nanonets, saving your AP team valuable time. Try it now!

Problem 1: Time-consuming manual data entry

Extracting invoice data manually is not just labor-intensive but also time-consuming. While paper-based invoices would require manual data entry, digital invoices, albeit a step up, still require someone to sift through the data and copy or extract the necessary information.

And on the off-chance that your ERP is not integrated with your invoicing system, your staff will have to manually enter the data into two systems, doubling the work and increasing the chance of errors.

The difference between traditional OCR and AI-powered OCR technology
AI-powered invoice processing is much smarter and neater than traditional options.

By combining OCR technology with AI, this process can now be completely automated. Invoices can be scanned, relevant data is captured and populated into the system.

This significantly reduces the time spent on data entry and allows your trade payable team to focus on more strategic tasks.

Problem 2: High error rate in manual data entry

Manual data entry is prone to human error. Even the most meticulous person can make mistakes when manually processing large volumes of data. These errors can lead to payment discrepancies, which can cause significant problems down the line, like financial discrepancies and weakened vendor relationships.

Setting rules to flag incorrect or suspicious invoice data
Setting rules to flag incorrect or suspicious invoice data

AI-based invoice processing drastically reduces these errors. Automating the data extraction process using ML and OCR eliminates human error in data entry. Any discrepancies are quickly flagged for review, preventing minor mistakes from becoming bigger issues.

Problem 3: Delay in invoice approvals

Delays could occur for several reasons — the approver might be busy, the invoice might get lost in a pile of paperwork, the invoice was routed to the wrong person, or there might be discrepancies in the invoice itself that need sorting out.

Your reason may be justified, but the result is the same — strained relationships with your vendors, delayed supplier orders, and potential late fees.

Automating the invoice approval workflow
Automating the invoice approval workflow

AI-based invoice processing streamlines the approval process. Each level of approval is mapped out in the system, ensuring that the invoice reaches the right person at the right time. Unapproved purchase orders can be tracked easily.

The AI can also flag discrepancies for review before routing the invoice for approval. And since payment processing is inbuilt into the AI system, the payment is processed promptly once approved.

Accelerate your invoice approvals now

Accelerate your invoice approvals now.

Streamline your approval process, ensuring invoices reach the right person at the right time. Say goodbye to approval delays!

Problem 4: Lack of transparency and control

Paper invoices can easily get lost; even digital ones can be misplaced in the sea of files. The lack of a central repository for all invoices makes it difficult to maintain an audit trail.

Moreover, it’d be tough to effectively implement 2-way matching (or even 3-way matching if required). This lack of transparency and control can lead to fraud and compliance issues.

Using AI-powered automation to make invoice-PO-shipment matching easy

Deploying AI in invoice processing creates a centralized system, making it easy to set up internal controls. You can set up 2-way or 3-way matching workflows more effectively. Detecting fraud and discrepancies becomes significantly simpler with AI as it can quickly identify patterns and irregularities in the data.

It also ensures that all invoices are stored securely with information on who reviewed and approved each one, increasing accountability and control over the process.

Problem 5: Difficulty in handling complex invoices

Invoices come in various formats, from scanned images to PDFs, and not all systems can handle these formats efficiently. This could lead to delays in processing or even loss of invoices, causing further frustrations and potential financial loss.

Manage all kind of invoice effortlessly with AI invoice processing
Manage all kind of invoice effortlessly with AI invoice processing

AI invoice recognition enables the system to identify and extract relevant data from scanned images, PDFs, and other digital formats using OCR technology and intelligent processing. The AI can also learn and adapt to different invoice layouts, languages, trade regulations, and currencies. These capabilities come in handy when dealing with international suppliers or complex purchase orders.

Handle complex invoice formats with ease

Handle complex invoice formats with ease!

Nanonets' intelligent invoice processing adapts to various formats, languages, and currencies. Simplify your complex AP workflows now.

Problem 6: Scalability issues with growing business

As your business grows, so do your transactions and invoices. Manual invoice processing can become increasingly unmanageable.

You’ll have to spend more time, hire more staff, or deal with more errors and inefficiencies as your business scales. This can put a significant strain on your resources and hamper your growth plans.

Process invoices in bulk with powerful integrations

AI systems can be configured to meet your growing needs without requiring additional human resources. You can easily onboard more vendors, process larger volumes of invoices, and handle complex transactions.

AI can also learn and adapt to your changing business needs, automating more tasks as required. Whether you're dealing with single or multi-line invoices or aiming to expand your vendor base, AI can scale up or down as necessary.

Problem 7: Difficulty in tracking and managing cash flow

Ineffective invoice processing can lead to cash flow issues. Without a clear view of incoming and outgoing payments, it can be challenging to manage your finances effectively. Late payments, missed payments, or even overpayments can lead to significant financial loss.

Payments made easy with AI invoice processing
Payments can be made easy with AI invoice processing

AI-based invoice processing gives you a real-time view of your financial status. The system can predict cash flow based on existing invoices and payment data, allowing you to plan your funds more effectively.

It also ensures timely payment processing, reducing the risk of late fees or missed payments. The AI can also flag potential overpayments, helping you avoid unnecessary costs.

Problem 8: Lack of interoperability

Not all systems can communicate with each other effectively. You may have an excellent invoicing system, but if it can't integrate with your existing financial software or ERP system, it can lead to inefficiencies and data silos. This lack of interoperability can create additional work, as data needs to be manually entered into multiple systems.

Connect to your existing accounting and ERP systems and seamlessly import, export, and sync invoice data
Connect to your accounting and ERP systems and seamlessly import, export, and sync invoice data.

With AI, you can automate entire processes across different systems. The AI can integrate with your existing software, enabling seamless data transfer and synchronization. This interoperability eliminates data silos and reduces the workload on your staff.

Moreover, AI is active 24×7, meaning it continues processing invoices and syncing data even after office hours, ensuring that your operations run smoothly around the clock.

AI for invoice processing helps businesses overcome many such common challenges in accounts payable workflows. However, it is crucial to keep in mind that not all AI-powered invoice processing systems offer all of these features. You should carefully review the capabilities of each system before making a choice.

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Streamline your procurement process with automated invoice data syncing. Nanonets captures invoice data and syncs it with your other ERP, accounting software, and inventory management tool, saving you time and effort.

How Nanonets' AI-based invoice processing can help?

Nanonets' AI for invoice processing combines OCR and AI technologies seamlessly to automate invoice processing. You can quickly train the system to recognize various invoice formats, layouts, and languages, making it suitable for businesses of all sizes and across industries.

Impact of Nanonets' AI invoice processing on Tapi's efficiency and cost-savings

Operational aspect Before Nanonets After Nanonets implementation Impact
Invoice Processing Time 6 hours per invoice 12 seconds per invoice Processing time reduced dramatically, enhancing productivity.
Operational Costs High due to manual processing Reduced by 70% Significant cost savings achieved by automating invoice processing.
Data Extraction Accuracy Reliant on manual entry, prone to error 94% accuracy with AI and automation Improved accuracy mitigated the risk of costly errors.
Invoice Volume Management Challenged by scale, hindering growth Effortless handling of 110,000 properties' invoices Enabled efficient scaling and supported business expansion.
Customer Experience Impacted by slow manual processes Enhanced due to rapid invoice turnaround Increased satisfaction with swift and reliable service delivery.
Resource Allocation Substantial time investment in manual tasks Resources reallocated to key business areas Allowed focus on strategic, value-adding activities.

New Zealand-based property maintenance company, Tapi, has harnessed the power of Nanonets to revolutionize its operational efficiency. Managing over 110,000 properties, Tapi faced the challenge of a slow, manual invoice processing system that hindered its growth.

From hours to seconds: Achieve similar results

From hours to seconds: Achieve similar results!

"Tapi has been able to save 70% on invoicing costs, improve customer experience by reducing turnaround time from over 6 hours to just seconds, and free up staff members from tedious work." - Luke Faulkner, Product Manager at Tapi. Schedule a personalized demo with Nanonets to learn how AI can streamline AP processing for your business.

Using Nanonets, they effortlessly captured crucial information from invoices, which were then sent to Tapi for checks and validation. The system proved reliable, with an impressive 94% data extraction and flexibility accuracy rate, enabling quick and seamless system integration.

The results were astounding. Manual processing, which previously took 6 hours, was reduced to just 12 seconds. The operational costs associated with invoicing plummeted by 70%, freeing up resources for other key business areas.

Tapi's automated invoice processing workflow after using our AI-powered invoice processing solution

The rapid invoice turnaround greatly improved Tapi's customer experience, demonstrating the transformative power of Nanonets' AI-powered invoicing solution.

Here’s how Nanonets can help your business, too:

Automated data capture: Capture and extract data from PDFs, images, spreadsheets, and other digital formats with ease. The AI invoice data capture capabilities eliminates the need for manual data entry, reducing errors and speeding up the processing time.

Seamless integration: Easily integrate with your existing software systems like Xero, Sage, Google Sheets, Gmail, Zapier, and others. This ensures seamless data transfer and interoperability, reducing data silos and enhancing operational efficiency.

Scalability: As your business grows, Nanonets can scale to meet your increased invoice processing needs. This flexibility ensures you can manage larger volumes of invoices without additional resources.

Intelligent processing: Leverage AI to understand and process complex invoices, regardless of layout, language, or currency. Nanonets intelligent processing can adapt to changing business needs, allowing you to handle more international vendors and complicated workflows.

Real-time analytics: Easily track the status of your invoices, monitor your cash flow, and make informed decisions based on accurate data.

24x7 operations: Invoice processing doesn't have to stop after office hours. The AI works round the clock, ensuring your invoices are processed promptly and your operations run smoothly.

Regulatory compliance: Automatically create audit trails and ensure all invoices comply with regulatory standards. This feature not only helps to maintain transparency but also makes it easier to remain compliant.

Cost reduction: Reduce operational costs by automating manual processing tasks. With a significantly faster processing time, you can lower your overhead expenses, leading to a healthier bottom line.

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Make invoices payment-ready faster.

Automatically capture and validate critical invoice data, such as PO numbers, line items, and payment terms, against your existing records. This ensures your invoices are accurate, complete, and ready for payment processing, saving your AP team valuable time and effort.

Nanonets AI invoice processing implementation guide

Getting started with Nanonets is straightforward. The interface is user-friendly and intuitive, and since it is a no-code platform, you don't need any technical expertise to set it up. 

Here's a step-by-step guide to implementing Nanonets AI invoice processing:

Step 1: Sign up and log in

Step 2: Choose or create a custom model

  • Select the pre-trained Invoice model for quick setup
  • For unique invoice formats, create a custom model:
    • Upload at least 10 sample invoices
    • Specify the data fields to capture
    • Annotate the fields on each invoice
    • Train the model and wait for email notification

Step 3: Configure your invoice processing workflow

a. Choose how invoices will enter the system:

  • Direct upload
  • Auto-import from email
  • Integration with cloud storage (e.g., Google Drive, Dropbox)

b. Configure data capture

  • The AI model automatically extracts key data fields
  • Review extracted data and correct inaccuracies to improve model performance

c. Define approval workflow

  • Establish approval rules and stages based on your requirements
  • Assign approvers to review flagged invoices

d. Set up the export process

  • Configure automatic export of approved invoices to your accounting software or ERP – Nanonets integrates with QuickBooks, Xero, SAP, and more
  • Use Webhooks or Zapier to trigger actions in your external systems upon invoice approval

Step 4: Test the model with sample invoices

  • Upload a batch of representative invoices
  • Verify the model's ability to handle various invoice formats and capture line item details

Step 5: Refine the model based on results

  • Review extracted data from sample invoices
  • Make corrections and retrain the model for improved accuracy

Step 6: Integrate with existing systems

  • Set up additional post-processing steps (e.g., matching extracted data with your database)
  • Export the processed data to your accounting systems, ERPs, CRMs, and databases using integrations, APIs, and Webhooks

Step 7: Upload real invoices

  • Deploy the workflow once satisfied with model performance
  • Start importing and processing real invoices through Nanonets

Step 8: Monitor performance and optimize

  • Monitor system performance and accuracy
  • Adjust the model and rules as needed to optimize the workflow
  • Continuously adapt the process to your evolving business needs

By following these steps and leveraging Nanonets' AI invoice recognition and data capture capabilities, along with its seamless integrations with various systems, you can quickly implement an automated invoice processing solution that streamlines your accounts payable workflow, reduces manual effort, and improves overall efficiency.

Final thoughts

AI-based invoice processing software are empowering businesses worldwide. It enables AP teams to shift from reactive to proactive roles, focusing more on strategic tasks than mundane data entry. While the upfront cost of implementing AI may seem high, its long-term savings and operational efficiencies make it a worthwhile investment.

As AI continues to evolve, so will its capabilities in invoice processing. The future promises more accurate data extraction, seamless system integration, and intuitive automation. AI invoice recognition will become increasingly sophisticated, enabling businesses to process invoices from a wide range of formats and layouts with minimal human intervention.

Remember, the success of implementing AI in your invoice processing depends on choosing the right solution that fits your business needs and goals. Take the time to review different options, understand their pros and cons, and make an informed decision. 

AI invoice processing FAQs

How to use AI for invoice processing?

You can use AI for invoice processing by leveraging tools like Nanonets that automate data capture, seamlessly integrate with existing software, scale with business growth, process complex invoices intelligently, provide real-time analytics, operate round the clock, ensure regulatory compliance, and reduce operational costs.

Can AI create invoices?

Yes, AI can create invoices by extracting and processing data from various digital formats. It can adapt to different invoice layouts, languages, and currencies, ensuring accurate and efficient invoice creation.

How do I automate invoice processing?

Invoice processing can be automated using AI technologies like Nanonets. It captures data, integrates with existing systems, scales as per business needs, provides real-time analytics, and ensures regulatory compliance.

What is generative AI for invoice processing?

Generative AI is where AI learns from existing invoice data to generate new invoices or process existing ones. It can be used for invoice processing in various ways: digitize paper-based invoices, extract data from multiple invoice formats, auto-populate or validate information, cross-check invoices, purchase orders, and inventory, monitor incoming invoices, and detect fraud. By automating tedious tasks, reducing errors, and improving efficiency, generative AI can optimize payments, manage cash flow effectively, and ensure compliance.

What is AI invoice processing?

AI invoice processing is the application of artificial intelligence to automate the capturing, extracting, and processing invoice data. This results in faster processing times, reduced errors, and improved operational efficiency.

How can AI help with invoicing?

AI can help with invoicing by digitizing documents, extracting data accurately, filling in data, cross-checking invoices, monitoring them automatically, and detecting fraud. By automating these tasks and improving efficiency, AI can optimize payments, manage cash flow effectively, and ensure compliance.

What is machine learning invoice processing? 

Machine learning invoice processing is a method of automating invoice data extraction and processing using machine learning algorithms. These algorithms learn from historical invoice data to improve their accuracy and efficiency over time, reducing the need for manual intervention in the invoice processing workflow. By leveraging machine learning, businesses can streamline their accounts payable processes and adapt to various invoice formats more easily.