AI-Assisted Data Capture Vs. Traditional OCR

AI-assisted data capture and traditional OCR applications are both capable of extracting data from various sources, such as documents, images, or scanned files. However, there are some significant performance differences between these two approaches. In terms of AI-assisted data capture vs. traditional OCR, let’s take a look at a comparison of the two applications to help you evaluate which solution may be best for your operation:

Accuracy

AI-assisted data capture systems generally outperform traditional OCR applications in terms of accuracy due to a number of different reasons.

  • Traditional OCR relies on predefined rules and templates, which may struggle with complex layouts, handwriting, or poor-quality documents.
  • AI-assisted data capture utilizes machine learning algorithms to continuously improve recognition accuracy, adapt to new patterns, and handle variations in data presentation.

Flexibility

AI-assisted data capture offers greater flexibility compared to traditional OCR applications.

  • Traditional OCR often requires specific configurations and customization to handle different document types effectively. This can be time-consuming and costly to set up.
  • With AI, the system can learn from a wide range of document types, formats, and languages, making it adaptable to different industries and use cases. It doesn’t require setting up specific documents in advance, as AI and ML help the system with learning.

Data Extraction

The main purpose of OCR is data extraction, making the effectiveness of this incredibly important. AI-assisted data capture systems can extract not only structured data but also unstructured information from documents.

  • Traditional OCR, while effective at extracting structured data, may struggle with complex layouts or unstructured content, limiting its capabilities.
  • AI-powered OCR can understand context and relationships, and even extract data from tables, check boxes, and handwriting.

Automation

AI-assisted data capture enables higher levels of automation. By leveraging AI algorithms, it can automatically classify and extract data from large volumes of documents without extensive manual intervention.

  • Traditional OCR applications may require more manual effort in setting up templates, defining rules, and handling exceptions.
  • AI-powered data capture can automate

Learning and Improvement

AI-assisted data capture systems have the ability to learn and improve over time.

  • Traditional OCR applications typically lack this adaptive capability and require manual updates to improve performance.
  • They can analyze user feedback, make adjustments based on new data, and continuously enhance recognition accuracy.

Integration and Scalability

While OCR doesn’t require AI in order to integrate into your systems or for scalability, it does help.

  • AI-assisted data capture systems can be easily integrated into existing workflows and systems through APIs, making them more scalable and compatible with various platforms.
  • Traditional OCR applications may require additional development efforts for seamless integration.

Conclusion

In terms of AI-assisted data capture vs. traditional OCR, overall, AI-assisted data capture surpasses traditional OCR applications in terms of accuracy, flexibility, data extraction capabilities, automation, learning, and scalability. It offers a more intelligent and efficient solution for extracting and processing data from a wide range of sources, consequently leading to improved productivity and accuracy in data capture tasks.

These differences are magnified in environments like accounts payable, where large volumes of documents of varying formats and quality have made the data capture process expensive, time-consuming, and manually intensive. While traditional OCR applications have provided some relief, the increased levels of performance from AI-assisted data capture solutions can drive game-changing efficiencies in AP and other document and transaction-intensive operations.

Contact ICG today to start a conversation on how ICG’s AI-assisted data capture solutions can deliver immediate value to your financial back-office. Or you can request a demo of one of our other solutions and see for yourself how your company can take advantage of the power of AI.

Posts you might like:

What’s Slowing Down Your Back Office (and How to Fix It)

Your back office handles the crucial processes that keep everything running: accounting, HR, compliance, and more. When these systems struggle, the entire organization slows down, impacting everything from customer satisfaction to your bottom line. So, what are the...

5 Questions to Ask Before Choosing New Technology

Choosing a new technology solution for your business is a big decision—one that can transform your operations or become a costly mistake. Before you sign on the dotted line for the latest "must-have" software, you need a clear, strategic framework. Here are five...

10 Ways to Reduce Costs in the Financial Back Office

The financial back office is essential for handling critical tasks like settlements, clearing, and regulatory compliance. In a competitive market, optimizing these operations is crucial for maintaining profitability and efficiency. Here are 10 actionable strategies...

Is a Bolt-On Solution Right for Your Back Office?

In the world of ERP systems and the financial back office, you might often hear the term "bolt-on" solution. But what exactly is a bolt-on, and is it the right move for your organization's financial operations? A bolt-on solution refers to a specialized, standalone...

Fixed And Dynamic Workflows

Not all automation is created equal. The two primary approaches, fixed and dynamic workflows, serve different purposes and play distinct roles in a company's operations. Understanding the difference between them is key to choosing the right tool for the job. What is a...

How Back-Office Chatbots Fuel Data-Driven Decisions

While chatbots are mostly known to be used for customer service, their potential within the financial and operational back office is rapidly growing. They're emerging as powerful tools for accessing, analyzing, and ultimately driving data-driven decision-making within...

The Impact of AI on Back Office Operations

The financial back office encompasses numerous crucial, historically time-consuming tasks that are prone to human error; however, with the aid of AI, these tasks may no longer be considered bottlenecks. AI is fundamentally transforming financial back-office functions,...

Multifaceted ERPs vs. ICG’s Solutions

Choosing the right back-office solutions can feel like navigating a maze. For businesses looking to optimize their back-office operations, the decision may come down to two entirely different solutions: a comprehensive, multifaceted ERP system or a more agile,...

Solution for Non-Standard Invoices

Invoice processing can be a major drain on resources for finance and accounts payable teams, especially when dealing with invoices that don't conform to a standard template. Manually keying in data from these non-standard documents is time-consuming, prone to error,...

Using a Vendor Portal to Consolidate Systems

Is your AP team constantly fielding calls and emails from vendors asking about invoice status? Are you juggling multiple backend systems, trying to provide a clear picture of payment progress? If so, you're not alone. Many companies, especially those with several...