Feature
Most businesses face the challenge of managing vast amounts of information embedded in documents across formats and sources. Intelligent document processing (IDP) is a way to address this challenge, allowing organizations to convert the data deluge into accessible and actionable insights.
By leveraging cutting-edge technologies, IDP not only streamlines the process of data extraction but also makes waves in decision-making processes and operational efficiency across sectors.
What Is Intelligent Document Processing?
Intelligent document processing refers to the use of advanced technologies, like artificial intelligence (AI), machine learning (ML) and optical character recognition (OCR), to automate the extraction and interpretation of information from various types of documents.
IDP transforms unstructured and semi-structured data into a structured format, allowing businesses to process large volumes of documents quickly and accurately.
How Does Intelligent Document Processing Work?
Intelligent document processing uses a multi-step approach to automate document handling. The steps are:
- Document capture: Documents are captured through digital scans or directly from existing digital files.
- Optical character recognition: This technology converts text images into machine-readable text, facilitating further processing.
- Data classification and extraction: Machine learning algorithms classify the text and extract relevant data by recognizing patterns and learning from ongoing interactions to improve accuracy.
- Integration: Organizations must integrate the processed data into business systems, making it accessible and actionable for further use.
“Document management has advanced greatly in the past 40 years when highspeed (60 to 90 pages per minute) cameras were used to produce document images on microfilm and microfiche,” said Mike Puscizna, IDP expert and former technical presales engineer at Kodak Alaris. Today, he added, high-speed scanners operate 220 pages front and back (440 images) per minute.
IDP also incorporates advanced intelligent character recognition (ICR), a type of OCR that can now translate different fonts and even handwritten text, said Puscizna, adding, “ICR results based on handwriting are amazingly impressive.”
Related Article: Time to Do a Spring Clean of Your Digital Document Silos
What Are the Benefits of Intelligent Document Processing?
IDP offers a host of benefits that streamline operations and foster business growth. Some key advantages include:
Improved Accuracy
Intelligent document processing greatly improves the accuracy of data extraction. By leveraging AI and machine learning, IDP systems learn from each interaction, continually refining their ability to recognize and process varied document formats and data types. This reduction in human error ensures that businesses rely on more precise data for their operations and decision-making.
Scalability
With IDP, businesses can handle large volumes of documents without a corresponding increase in staff or resources. This scalability is crucial for organizations experiencing growth or those with fluctuating document processing needs.
Cost Reduction
IDP technology significantly reduces operational costs through decreased labor, minimized errors and reduced need for physical storage space. However, Alan Pelz-Sharpe, founder of Deep Analysis and co-author of “Practical Artificial Intelligence — An Enterprise Playbook,” said in a BrightTALK webinar that cost-cutting is the worst reason to adopt intelligent document processing solutions. Instead, it should be about making a business more effective.
“Find business processes that don’t add a whole lot of value and that you can automate,” he explained. “If a machine can do it better (not as well as), then we should automate it.”
Improved Compliance
IDP systems are designed to adhere to regulatory standards and automatically update to comply with new legal requirements. This compliance is crucial for industries such as finance and healthcare, where handling sensitive information with precision and security is crucial.
Better Customer Experience
Intelligent document processing allows businesses to respond more quickly and accurately to customer inquiries and requests. This efficiency can significantly enhance customer satisfaction, as clients receive faster, more accurate service.
What Are the Use Cases of Intelligent Document Processing?
“Today, capturing documents is not just about archiving but additionally unlocking all the data within the documents,” said Puscizna. “Documents in today’s world include images, emails, email attachments, fax and documents of all format types.”
Workflows can be configured during capture to add advanced processing such as automated imports, image enhancement, database lookups, validations of data, triggers that require human intervention, customized exports to other platforms and more complex steps that can be configured via scripting.
The most common use case for this technology, according to Pelz-Sharpe, is invoice processing. Broken down by industry, other common use cases include:
- Insurance: Processing claims, underwriting policies and customer onboarding documents.
- Legal sector: Managing case files, contracts and other legal documentation.
- Government: Processing applications for permits, tax documents and identification papers.
- Logistics and supply chain: Managing shipping documents, invoices and freight bills.
- Human resources: Processing employee documents, including resumes, onboarding paperwork and employee records.
The processing methodology is different for different applications, Pelz-Sharpe explained. “For invoices, every invoice goes through the same process — unless there’s a big exception.”
When you get into contracts and emails, he added, that’s when you get into human reasoning. “There will be a process, but it’s got so many more options in it and types of exceptions, it’s much more nuanced and more dependent on the skill of the human. It’s not just data checking. But there’s usually always a structure of sorts — one is very regimented, the other is more ad hoc.”
Related Article: AI Is Here to Help. Recruiters Aren't So Sure
What’s the Role of AI in Intelligent Document Processing?
AI has transformed the IDP market, said Pelz-Sharpe. And, he told Reworked, he believes big changes are still to come.
“That’s in large part because the newer IDP vendors all honed in on well-established use cases like accounts payable and receivable. It’s only now we are starting to see some, often in combination with RPA [robotic process automation], take on new use cases in healthcare, supply chain, government, etc.”
Sadly, added Pelz-Sharpe, too many of the new solutions entrants end up fighting over the same opportunities. And with funding tight for startups, there is likely to be a fallout of sorts.
“So, to be clear, the biggest changes we are seeing are the merging of process and task automation with IDP — which makes perfect sense, opens up more new business opportunities –- but bizarrely, this was relatively uncommon till recently.”
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Webinar
On demand
From Hype to High-Impact CX Strategies That Actually Scale
Turn buzzworthy AI and outsourcing trends into measurable CX wins with fresh 2025 data.
Watch Now
Webinar
On demand
Insights to Action Rethinking the Contact Center for Real Business Impact
Join our exclusive webinar to hear CX executives share their innovative strategies for transforming service delivery.
Watch Now
Webinar
On demand
Accelerating Healthcare Ops with AI
Sign up to see how your peers are putting AI to work — and making it stick.
Watch Now
Practical Advice for Adopting an IDP Solution
One of the biggest and most common challenges in adopting IDP is the change management work that needs to be undertaken, explained Pelz-Sharpe.
“In most cases, IDP software is linked to complex business processes, so even if modern IDP systems are fast and accurate, you still have to change working practices, integrate with existing systems and often replace older capture systems.”
It’s like any other enterprise software, he added — you can’t just plug it in and walk away. You need to manage and control a project.
Some practical advice he offered for brands looking to adopt an IDP solution?
“Think of ways you can run your business more effectively. Test what’s out there now, even if you don’t plan to adopt solutions for a couple of years. Educate yourself. Don’t replicate the way you worked before. Think it through and think of a better way of working. AI allows you to redefine your business processes.”
Emerging Trends for IDP in Next 5-10 Years
In the next five to 10 years, IDP will most likely merge into the infrastructure as a necessary component for everything from generative AI to traditional document processing, said Pelz-Sharpe.
“That’s quite exciting, as until relatively recently extracting data accurately from files was doable but often hard and expensive to do well.”
If you look at what Adobe and Microsoft are doing with AI, he added, you can see IDP elements simply being bundled as standard functionality. “There will also be a high and exclusive end of the market, but we are going to see much more widespread use of IDP technologies to support a huge array of business activities.”
Ultimately, he explained, IDP might fade from the analyst spotlight, but it will grow exponentially as part of the mainstream.
