Unveiling AI’s role in document processing and data extraction

Artificial intelligence can transform massive volumes of unstructured  content into actionable  information by automatically capturing, classifying and separating documents and extracting vital data and providing it to the enterprise systems and processes that need it. It can help you isolate text and transcribe complex data layers without manual labor and reach across your entire enterprise by. This automated data extraction layer unifies fragmented information across legacy ecosystems to fuel downstream automation engines.  

• Eliminating operational bottlenecks: AI-driven intelligent capture removes repetitive manual data work to shorten business cycles and lower operating costs per transaction.  

• Automating multiformat extraction: Advanced capture mechanisms accurately identify and extract field-level text, optical marks, handwriting and document metadata to reduce manual validation loops.  

• Enabling agentic enterprise: Accurate, context-enriched extracted data fuels agentic automation and intelligence at enterprise scale.

Integrating AI into document processing enables automation systems to recognize, interpret and extract information with human-like comprehension. By utilizing natural language processing (NLP) technology, these intelligent capture systems analyze unstructured text, interpret context and meaning and isolate critical data points within complex layouts. 

An essential element of this workflow is data extraction, which leverages large language models (LLMs) to captures targeted information from semistructured and unstructured files. Converting untamed content into structured data feeds downstream automation engines to streamline high-volume workflows, including financial transactions or contract management, while eliminating manual data entry errors. 

> Read more | Navigating the pros and cons of unstructured data

Automation works well for structured data, but what about unstructured data like image files, audio files or text documents?

Enter the AI-powered intelligent capture solution. With advanced technology components like NLP. LLMs and optical character recognition (OCR), it can automatically recognize, extract and convert semistructured and unstructured data — making it a versatile document processing tool for various industries.

To truly automate document-heavy workflows, an automation engine must be capable of extracting more than just standard typed text. Modern data extraction technologies pull actionable insights from multiple layers within a single document, transforming messy inputs into structured, machine-readable data.  

By deploying advanced extraction capabilities, organizations can capture several distinct types of data: 

• Optical marks: This includes checking for the presence or absence of marks in checkboxes, radio buttons, stamps and signature blocks. Automatically detecting these marks accelerates validation loops in applications, consent forms and contracts without requiring manual human reviews.  

• Field-level data: This targets specific, high-value strings within a document, such as invoice numbers, purchase order dates, totals and customer IDs. Isolating these fields allows enterprise systems to automatically populate databases and execute downstream financial or operational tasks.  

• Image-based data: This extracts data contained in non-textual elements like photos, diagrams, logos or other embedded graphical elements. Capturing these elements allows companies to automate and accelerate processing of visual information such as photos of damage in an insurance claim.  

• Document metadata: This focuses on the hidden administrative data linked to a file, including the author, creation timestamp, revision history and geotagging strings. Systematically extracting this data is critical for compliance and security workflows, as it allows organizations to audit file origins or programmatically strip sensitive tracking details before files are shared or archived.  

• Intelligent character recognition (ICR): This uses advanced recognition engines to interpret and transcribe handwritten text from scanned forms, doctor notes and historical records. Converting handwriting into digital text bridges the gap between legacy paper workflows and modern cloud automation.  

The value of multitype extraction

When you automate the extraction of these diverse data types simultaneously, you lower the cost per transaction, eliminate manual data validation bottlenecks and ensure that downstream business applications are fueled by clean, highly accurate enterprise intelligence. 

Intelligent document processing (IDP) solutions like Hyland IDP use intelligent capture, AI models to consistently improve automation, efficiency and accuracy, providing ongoing value to businesses. It’s important to highlight the integral role AI plays in carrying out IDP operations. Here’s the breakdown of IDP’s capabilities when enhanced with AI tools:

> Read more | What's the difference between AI and ML?

AI-powered IDP is a crucial tool to enhance operational efficiency and cost effectiveness. By reducing the need for manual processing and human intervention, IDP minimizes errors and streamlines workflows, resulting in enhanced productivity.

More specifically, AI-powered IDP offers a host of benefits to businesses, including:

Efficiency and speed

AI’s LLM, OCR and NLP capabilities — combined with intelligent capture — enable IDP solutions to automatically and accurately identify hundreds of various document types. This significantly reduces time and effort in manual data entry, especially for large data sets.

For example, in manual insurance claims processing, claims adjusters personally review and process paper or electronic claims documents. This could potentially cause delays, errors and consequently multiple rounds of revisions, especially with high volumes involved or a distributed workforce.

AI-powered IDP systems extract and verify data from claims documents, accelerating the claims processing timeline and reducing administrative overhead.

Accuracy and consistency

IDP solutions can eliminate human error in data extraction and processing, as well as automatically adapt to new data and document types.

This is useful in cases like HR document processing and management, where employee information can automatically be extracted from resumes, identification documents and other HR-related documents.

This reduces errors in data entry — or even the need to manually input data — as well as ensures consistent handling of employee data and streamlines the onboarding process and end-to-end employee journey.

Scalability and adaptability

AI-powered solutions can support large volumes and changes in documents (including types and formats), and scale to handle different business needs.

Government document processing deals with a variety of high-volume documents (such as permits, licenses and public records), which come with changing regulations.

IDP can help government agencies process and categorize these documents efficiently, as the system can scale to handle a high volume of documents and adapt to changes in regulations or document types.

> Read more | 5 reasons government agencies turn to IDP

System integrability

AI-powered IDP can integrate with existing systems and workflows, making it easier for businesses to adapt without disrupting their operations.

Take accounts payable (AP), a crucial component of a business’s financial operations that involves the management and processing of invoices, payments and other financial transactions. With its many necessary documentation requirements (like invoicing) and approval workflows, AP can become a daunting and time-consuming task.

When an AP system integrates with AI-powered IDP, the extraction and validation of invoice information can be automated. This integration accelerates invoice processing, reduces errors and enhances overall efficiency.

Cost-effectiveness

The above benefits, combined, can lead to increased operational efficiency, lower required manpower volume and subsequently, substantial cost savings for businesses.

Download now | Content, automation and AI transformation with Forrester study insights

AI-enabled IDP has extensive applications across vertical sectors. It can seamlessly integrate with business solutions such as customer relationship management (CRM) and enterprise resource planning (ERP) platforms, which enhances decision-making and data analytics capabilities across industries including:

Financial services

Modern IDP systems leveraging AI improve current workflows and systems within financial services, such as loan and mortgage processing, and can enhance future process outcomes.

Employees gain quick access to all data that has been scanned into a digital system. In turn, customer service improves as staff can locate data easily, accelerate decision-making and provide timely responses to inquiries.

Loan and mortgage processing are subject to regulatory requirements which involve thorough documentation and verification of financial information. AI-enabled IDP helps organizations avoid penalties, legal issues and more through ensured regulation compliance, and by performing advanced document analysis to identify potential fraud.

Companies can also work with updated data insights to further support risk assessment, trend analysis, portfolio management and continued compliance — gaining a competitive edge and maintaining a trustworthy customer image.

> Read more | Modernization, automation and AI in financial services

Insurance

AI-powered IDP enables companies to work through various steps of the insurance workflow, including claims and policy processing.

IDP systems can support underwriting with timely and accurate information, which increases data accuracy, reduces human error and speeds up decision-making by providing staff with quick access to digitized data.

Like financial services, AI-enabled IDP systems help insurance companies reduce risk by ensuring compliance with regulatory requirements and bolstering fraud detection through advanced document analysis.

IDP systems are scalable, meaning they can handle increased or decreased document volumes by efficiently allocating resources to ensure optimal performance without compromising efficiency.

In this way, insurance companies also benefit from reduced costs (associated with manual document processing), as well as additional data insights that can support risk assessment, trend analysis and portfolio management to gain a competitive edge and customer trust.

Healthcare

IDP systems powered by AI enhance healthcare services in several ways, including providing access to and management of medical records, automating patient referrals and handling medical insurance claims.

In today’s competitive healthcare system, it’s crucial to provide timely patient care to gain market lead. AI-powered IDP gives care providers access to current digitized patient data, handling both structured and unstructured medical formats.

In addition, practitioners can access large volumes of historical records in real time — supporting patient data analysis, developing tailored solutions for individual cases and identifying patterns in healthcare cases for diagnostic purposes. It can also support telemedicine through processing documents from virtual appointments.

AI can also automate medical bill and claims processing, eliminating cost related to manual processing. Through AI-powered IDP, care providers are able to provide efficient, low-cost healthcare — making them a top choice for patients.

Higher education

AI-enabled IDP streamlines administrative tasks within the higher education sector, including the admissions process and student record management.

When education institutions use IDP systems to gain access to digitized data, they’re able to respond quickly to student inquiries — this creates a positive impact for recruitment efforts among potential students and increases engagement and retention rate among current students.

Administrative tasks can also be streamlined through automated document processing, smoothening the admissions process.

With that, administrative and support staff can focus on higher-value activities, including branding and recruitment. They can also make use of data insights to support planning, student performance monitoring and overall efficiency.

> Read more | The role of AI in transforming higher education

Government

State, regional and federal governments receive a large volume of citizen, constituent and agency enquiries, many of which relate to tax and compliance, and may require access to public records.

AI-powered IDP automates document processing and classification, improving record management and streamlining citizen services. This is vital for governments when accelerating decision-making to citizen and agency inquiries, especially in cases that require emergency response related to public safety.

Governments also rely on transparency and strict compliance to implement effective policies, earn public trust and maintain fairness, equity and stability.

AI-powered IDP can help government institutions adhere to regulatory requirements and support emergency cases like disaster recovery through digitized, highly available records that have been vetted through for accuracy and fraud.

Ultimately, this ensures a more secure and efficient environment for citizens while strengthening trust between public institutions and the people they serve.

> Read more | AI in the workplace

Intelligent capture, enhanced by AI, takes automated data capture to a higher level, capturing and extracting the right information, and making sense of a variety of documents without manual intervention.

With AI document processing, employees can focus on higher-value tasks while systems work to identify and extract information automatically from complex documents. It’s a win-win all round: Staff experience increased productivity and job satisfaction, and companies benefit from streamlined processes, improved accuracy and lower operational costs.

Hyland IDP is a prime example of advancement in AI-powered data processing and extraction. Its comprehensive features and functionalities automate document capture, classification and data extraction — maximizing AI’s potential to revolutionize document processing in the digital age.