How to Use AI to Extract Data from PDF: Benefits & Use Cases

The excitement around AI and its massive potential has energized organizations to rethink their approaches at every level of business. One popular use case is AI to extract data from PDF files. PDF, short for portable document format, is a ubiquitous format used for reports, invoices, statements, and many other types of documents.

In fact, every business deals with PDF files regularly, with an estimated 82% of businesses using PDF as their primary document storage and sharing format and trillions of new PDF files being created every year. Despite their ubiquity in document storage and sharing, PDFs pose certain challenges when it comes to data extraction. However, AI-powered solutions are primed to tackle these challenges, with AI making data extraction from PDF documents more accurate and seamless than ever before.

This blog looks at the benefits of using AI to extract data from PDF, how it works, and the most popular tools and use cases.

Out with the Old: 4 Challenges of Conventional Data Extraction for PDFs

Most companies use different combinations of manual and conventional data extraction approaches to manage their PDFs. However, these approaches pose certain challenges that can be overcome with AI-powered data extraction. Let’s briefly look at what they are:

1. A large percentage of business data goes to waste: 68% of data created by businesses is not utilized at all, and a considerable share of this untapped data is locked in PDFs, arguably due to the challenges of accurately extracting data from PDFs.
2. Conventional data extraction is error-prone and slow: The error rate associated with manual data extraction can be as high as 5 to 10%. Apart from the accuracy, the manual approach isn’t a practical option considering the high volume of PDF files that an average business deals with regularly. Similarly, for semi-structured and unstructured PDFs, even the best conventional extraction tools have a 1% error rate. This may not seem like much, but in a 10,000-word PDF file, the 1% error rate signifies as many as 100 errors.
3. Conventional data extraction tools struggle with semi-structured and unstructured PDFs: Data extraction tools struggle with semi-structured and unstructured PDFs due to inconsistent layouts, complex designs, and the challenge of interpreting context without clear patterns. Encoding issues in PDFs and limitations of current technology for scanned documents can further complicate extraction, especially if the text is fragmented, mislabeled, or handwritten.
4. Extracting tables from PDFs is even more challenging: So far, we’ve discussed the extraction accuracy of PDFs containing only text data. When you throw tables into the mix, accurate data extraction becomes more challenging as the estimated accuracy rate drops to 80-90%. This is because of their complex and varied layouts, as PDFs store data as visual elements rather than structured formats, so tables may appear as images, making it challenging for extraction tools to identify rows, columns, and relationships between cells.

How to Extract Data from PDF Using AI: 5 Basic Steps

AI data extraction refers to the use of AI to automatically extract relevant data from unstructured data stored in formats such as PDF. It typically utilizes large language models (LLMs), such as GPT-4o and Claude 3.5, and technologies like natural language processing (NLP) and retrieval-augmented generation (RAG) to automate the data extraction process.

While the exact process can vary depending on the specific solution and use case, AI-powered data extraction tools typically follow these basic steps:

Text Recognition with AI-Enhanced OCR

OCR, short for optical character recognition, is a technology used for recognizing and extracting text from pictures and scanned documents. In other words, OCR converts your PDFs into searchable, editable data. AI enhances OCR by enriching data, improving accuracy, recognizing multiple languages, and understanding the document structure beyond basic text recognition.

Data Preprocessing

Once raw data has been collected, preprocessing requires cleaning and organizing it by removing noise and irrelevant data and standardizing the formats to ensure consistency across different data types. Data preprocessing is a crucial step in helping transform raw data into a format more suitable for AI and ML algorithms.

Data Extraction Using NLP & IDP

The data extraction step involves the use of AI technologies like NLP and IDP for the identification, classification, and extraction of data from PDFs. NLP, short for natural language processing, helps AI understand the context and meaning of the extracted data. Similarly, intelligent document processing (IDP) leverages AI to accurately extract data while also keeping the relationships and logical structure of the document intact.

Data Validation

Once the data has been extracted, validation is necessary to ensure data accuracy and integrity. This can be done through data quality checks and pre-defined rules to confirm the output is free of errors or inconsistencies.

Data Integration

After validation, the output is integrated into the relevant systems, such as analytics or business intelligence (BI) pipelines or target databases, so that the data can be converted into insights for decision-making.

Read more: How Garnet Enterprises automates PDF data extraction for time and cost savings.

Making the Case for AI: 6 Benefits of AI Data Extraction for PDFs

Using AI to extract data from PDF offers several benefits in the way of efficiency, accuracy, and cost reduction. Let’s look at the biggest upsides of using AI for data extraction:

Improved Accuracy

While the accuracy rate for PDF data extraction varies between solutions, an accepted range is 90-95%. However, AI-powered data extraction can offer an average accuracy rate of up to 99%. As we discussed earlier, even a slight increase in accuracy can lead to substantial cost and resource savings while also improving the overall quality and reliability of the data. For instance, Astera’s AI-powered data extraction solution can reduce errors in data extraction by 97%.

Increased Efficiency

Compared to manual processing and conventional data extraction solutions, using AI to extract data from PDF documents can automate many of the repetitive tasks for faster processing. SHRM reports that 80% of users who have adopted AI are seeing increases in efficiency. More specifically, solutions like Astera offer up to 90% faster data extraction from PDFs and 8 times faster document processing overall.

Cost and Time Savings

The increased accuracy and efficiency, coupled with AI automating much of the work involved in extracting data from PDFs, leads to substantial cost and time savings. PwC reports that even the most basic AI-based data extraction can save organizations 30-40% of the time typically spent on data extraction. The time saved also translates to cost savings and resource optimization for the organization.

Better Compliance

When it comes to extracting data from PDFs, use cases involving medical records and financial documents are also subject to strict regulations such as GDPR and HIPAA. AI-powered data extraction from PDFs improves data integrity, which in turn improves compliance with the relevant regulations.

Scalability

The amount of work involved in conventional data extraction techniques poses a challenge for organizations looking to scale. However, AI’s ability to process large volumes of PDFs in a considerably short time span solves this problem. As a result, AI empowers growing organizations to drastically increase their data extraction capabilities if needed.

Flexibility

AI’s ability to self-learn is an underrated benefit of leveraging it for data extraction from PDFs. For organizations working with PDFs containing different document types and varying layouts and formats, AI can adapt to the changes for improved efficiency and accuracy.

Extract thousands of PDFs accurately and quickly with Astera

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4 Popular Use Cases of AI to Extract Data from PDF Files

AI is finding applications in almost every function, thanks to the different types of PDF documents it can process. For brevity’s sake, let’s look at some of the more popular use cases where AI-powered data extraction fits like a glove:

Insurance Claims Processing

Insurance companies process hundreds to thousands of claim forms on a daily basis. These claims are filled out by customers and are typically in PDF format. Each claim form contains crucial information such as policy type and number, customer details, address, claim amount, and much more. As one can imagine, manually transcribing this information will be an error-prone and time-consuming process, especially considering the high volume of claim PDFs processed on a daily basis.

By leveraging AI to automatically extract the relevant data, insurance companies can process claims swiftly to improve operational efficiency and customer satisfaction.

Read more: How Aclaimant reduced time spent on Claims Processing by 50%.

Invoice Data Extraction

Depending on the size of the business, organizations have to handle anywhere between several hundreds to thousands of invoices every month. One big challenge with processing invoices is that one person’s delivery in two weeks can be another’s delivery in 14 days.

In other words, the smallest of variations can lead to huge discrepancies, which is why AI-powered data extraction is tailor-made for invoice processing. By analyzing and understanding the context and meaning of data, it can accurately process invoices.

Read more: How a US Govt Dept took PDF Invoice Processing time from hours to seconds.

Purchase Order Processing

Much like invoices, purchase orders (POs) are a crucial document for many SMBs and enterprises. A lot depends on swift purchase order processing, which is why it’s a prime candidate for AI data extraction. Organizations typically receive purchase orders through emails in the form of PDFs. Similar to invoices, POs contain a lot of crucial and pertinent information in transaction details, such as item descriptions, delivery dates, quantities, agreed-upon prices, and payment terms.

Thanks to AI data extraction, all these details are extracted accurately and swiftly, enabling quick turnaround times, increasing operational efficiency, and improving customer satisfaction.

Read more: How Ciena Corporation extracts data from Purchase Orders 15 times faster.

Contract PDFs Extraction

The challenge of extracting data from PDFs isn’t just in the varying formats. For instance, businesses and firms also have to process contracts containing hundreds of pages and thousands of words. Plus, to make matters worse, most of the time, these contracts aren’t editable or even searchable. Going through a single one of these contracts to find the pertinent information can take hours.

With AI-powered data extraction, organizations can convert their contract PDFs into searchable data to find the exact information they need. This, of course, leads to considerable time and cost savings while also increasing operational efficiency.

Read more: How a Manufacturing Firm Processed 40,000 PDF Contracts in Under 4 Days.

Extract Data from PDFs in Seconds with Astera

To summarize our discussion so far, PDFs are crucial in every aspect of business and will remain so for the foreseeable future. Organizations that can extract data from PDFs accurately, swiftly, and comprehensively will gain a competitive edge. AI is making this a reality by enabling automated data extraction that is far more accurate and efficient than conventional extraction tools.

At Astera, we believe in AI’s potential for getting work done much quicker and more accurately. With Astera’s AI-powered document processing solution, organizations can get more done in less, converting raw data locked in their thousands of PDFs into actionable insights within seconds.

Astera’s intelligent document processing (IDP) solution stands out because it offers:

• 90% faster data extraction than conventional solutions on the market,
• 97% reduction in errors while extracting data from PDFs,
• 90% faster data preparation for quick analysis and decision-making,
• 8 times faster document processing for maximum efficiency.

Get the most out of your PDFs with Astera. Talk to an expert to see how.