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Intelligent Document Processing: How AI is Revolutionizing Business Workflows

· 3 min read
AI extracting data from business documents

Intelligent Document Processing (IDP) is emerging as one of the hottest trends in business process automation in 2020. As organizations grapple with mountains of unstructured data—think invoices, contracts, emails, and reports—AI-powered IDP holds the promise of extracting valuable information faster, more accurately, and at scale.

Why Intelligent Document Processing Matters in 2020​

The COVID-19 pandemic has forced businesses to accelerate digital transformation, driving urgent demand for remote-friendly, touchless processes. However, traditional automation often falls short when handling unstructured data. Manual review of documents is slow, error-prone, and expensive.

IDP technologies bridge this gap by applying artificial intelligence (AI), machine learning, and natural language processing to ingest, classify, and extract data from a variety of document types. This means:

  • Faster business cycles, as approvals and reviews are streamlined
  • Higher compliance, owing to less human error
  • Substantial operational cost savings

How Does IDP Work?​

Unlike basic document scanning or OCR, IDP solutions combine several AI components:

  • Document Ingestion: Captures files from emails, folders, or physical scans
  • Classification: Automatically detects document type (invoice, purchase order, contract, etc.)
  • Data Extraction: Identifies and pulls key data points—like dates, amounts, signatories
  • Validation: Cross-checks extracted data and flags discrepancies
  • Integration: Passes structured data into ERP, CRM, or workflow tools

In 2020, leading vendors such as ABBYY, Kofax, and IBM are racing to enhance their IDP offerings, often with pre-trained models for common documents in finance, insurance, and healthcare.

Real-World Use Cases​

IDP is not just theory—it’s already delivering ROI in multiple industries:

  • Accounts Payable Automation: Automating invoice entry, verification, and payment approval, freeing up finance staff for more strategic work.
  • Claims Processing in Insurance: Rapidly extracting claimant data, policy info, and loss details from forms and correspondence.
  • Onboarding New Clients: Speeding up customer due diligence by processing identity documents, contracts, and financial statements automatically.

Example: In 2020, a leading European bank deployed IDP to automate more than 70% of incoming new account applications, reducing manual effort by 60% and cutting processing time from days to minutes.

Key Benefits for Forward-Looking Businesses​

By automating document-driven processes, enterprises can:

  • Reduce costs related to data entry and manual reviews
  • Improve accuracy with AI validation and detection of anomalies
  • Deliver better customer experience with faster turnaround times
  • Achieve compliance by standardizing key data handling and audit trails

Getting Started with IDP​

For organizations ready to adopt IDP in 2020, consider these best practices:

  • Assess your process: Identify where unstructured data slows down workflows
  • Start small: Pilot with documents that are high-volume and repetitive
  • Choose flexible solutions: Look for platforms that can scale and adapt to new document types
  • Plan for change management: Train teams to collaborate with the new AI-powered workflows

Conclusion​

Intelligent Document Processing is a powerful enabler for modern business automation, especially as remote work becomes the new normal. Organizations that embrace this technology in 2020 will outpace competitors by unlocking the value trapped in their documents—turning data mountains into actionable insight.