The false promise of point solutions
Intelligent document processing (IDP) promised a paperless future for businesses and organizations. But despite significant investment, a critical gap often persists between the technological capability to extract data and the organizational ability to actually drive meaningful business outcomes.
78% of enterprises are now operational with some form of AI-powered document processing, yet 52% of staff time remains consumed by manual document tasks.1 This paradox reveals the new IDP market reality: The primary bottleneck is no longer optical character recognition (OCR) accuracy, but the lack of integration between extraction tools and the broader end-to-end business process.
Escaping the automation silo
Many enterprises attempt to patch AI on top of document-heavy workflows that were originally designed for paper-based operations. In fact, 53% of organizations identify process redesign as a major hurdle in their IDP journey. Rather than rethinking the process end to end, they automate a single workstream. Automation stops once the data is extracted. The worker must still validate the data integrity, cross-reference data across enterprise systems like ERPs and CRMs, and manually execute the next step in the workflow.
When document processing is treated as a standalone step, it creates automation silos—isolated pockets of efficiency that do not communicate with upstream data sources or downstream decision engines. This leads to breakdowns in employee experience, forcing swivels between systems of record and standalone automation tools.
Don’t stop at extraction
Effective IDP doesn't just read documents, it automates end-to-end document workflows.
Weaving document processing directly into business workflows transforms it from an external service into a native capability that can:
Eliminate automation silos. Native IDP ensures the data extracted from your documents flows instantly from intake to resolution without manually plugging it into the next step.
Validate data. Connect downstream systems end-to-end, validating and enriching extracted data against enterprise records.
Manage exceptions. When confidence is low, the system routes the document to a human for rapid reconciliation.
Ensure transparency. Every action is recorded in a single, unified audit trail, ensuring compliance in highly regulated sectors.
The DocCenter approach
Appian leads the market in automating end-to-end document processing. Appian reimagines document automation as a native capability of a unified platform, rather than a bolt-on tool. Our solution, DocCenter, enables data to flow instantly into downstream functions—from intake to resolution.
Value Driver | Point Solution Approach | DocCenter’s End-to-End Approach |
Automation Scope | Task-only extraction digitizes the document and then stops, creating automation silos that require manual pass-off to other systems. | End-to-end automation within a single environment. No complex and costly integration of disparate tools. |
Data Context | Extracted data exists in a vacuum without the business context needed to validate or enrich it against enterprise systems. | Extracted data is enriched by the business context and intelligently stored in Appian’s data fabric for secure, performant access. |
Exception Handling | Exceptions handoff to humans with no governance, tracking or audit trail, often leading to manual rework outside the system. | High-transparency models allow for rapid reconciliation that improves accuracy, driving higher straight-through processing rates. |
Auditability | Fragmented audit trails require manual stitching between extraction tools and core applications, creating security holes and compliance risks. | Full transparency at every decision point in the workflow with a unified, seamless audit trail that inherits platform-grade compliance for ISO, HIPAA, FedRAMP, and more. |
Native IDP in action
So what does this actually look like in practice? Document data serves as the foundational trigger for many enterprise actions, so embedding IDP in an end-to-end process can transform operational efficiency across every business domain. Here are some examples:
Supply chain management
Procurement. Enable workers to accurately capture data and update as needed through the negotiation process. After negotiation, data can be approved once, and then automatically uploaded into enterprise systems.
Logistics orchestration. Extract data from complex, multi-page shipping artifacts such as bills of lading, customs forms, and proofs of delivery. By fitting IDP into a process, organizations can connect data with workstreams to provide real-time visibility across the entire shipping lifecycle.
Order intake management. Ditch manual, error-prone order entry. Extract line-item data from purchase orders or handwritten forms, feeding it directly into inventory management systems without human intervention.
Appian customer story:
A leading global health technology company automated their order management process with Appian. The system receives incoming orders, extracts the data, executes a quote verification, and seamlessly routes it for processing. This resulted in 95% automation of the order-intake process and a 30% reduction in overhead costs.
Finance and accounting
Loan processing. Eliminate friction between application intake and credit decisions. Validate extracted data from application documents against external databases and automatically route the completed file to a decision engine.
Procurement. Streamline vendor management by classifying and extracting data from supplier agreements and W-9s. Integrate the data into the broader financial workflows, reducing the risk of payment delays or compliance gaps.
Accounts payable. Replace manual data entry with AI-driven extraction that integrates directly with ERP systems to automate the entire invoice-to-pay cycle. Validate data against purchase orders and vendor records in real-time while maintaining a full audit log.
Appian customer story:
Century Fire Protection was experiencing challenges with their 100% manual accounts payable process. Appian’s IDP solution delivered simple interfaces and integrations, accessible to a non-technical workforce. The customer successfully runs 85 processes on Appian. They achieved a 70% reduction in manual interventions and a 50% decrease in missed discounts.
Insurance processes
Underwriting. Accelerate risk assessment by automatically extracting data from medical records, safety certificates, and complex applications. Provide underwriters with the situational context needed to make faster, more accurate premium decisions.
Claims adjudication. Streamline the end-to-end claims lifecycle by automating the ingestion of first notice of loss (FNOL) forms and supporting evidence. Automatically validate claim data against policy terms and trigger automated resolutions or guided human reviews for faster settlement.
Appian customer story:
Australia’s largest general insurer deployed Appian to transform their commercial underwriting operations. The solution streamlines the ingestion of complex, unstructured broker submissions by allowing underwriters to accurately review, assess, and price policies. This has boosted accuracy to 99% and reduced the average time per quote from four days to less than 90 minutes.
Legal and GRC
Contract management. Use generative AI to reason through lengthy, unstructured legal contracts and identify renewal dates, liability terms, and obligation clauses. Once extracted, the system can automatically update contract repositories and launch notification workflows.
Compliance audits. Accelerate audit cycles by applying automated business rules to check extracted document data. This approach reduces audit backlogs, increases straight-through processing rates, and cuts processing times.
Appian customer story:
Acclaim Autism automated patient onboarding with Appian. Using AI-powered document extraction, they cut onboarding time from an average of six months to just four days. Patient intake increased by 15x, insurance submission accuracy rose to over 95%, and rejection rates dropped from 80% to just 5%.
Customer service
Identity verification and intake. Verify identity documents for highly regulated processes like KYC in financial institutions and patient intake at healthcare firms. Ensure solutions meet strict federal and local regulations such as HIPAA or AML requirements.
Case management. Ingest customer emails and attachments, classify the intent, and extract relevant data to populate case records instantly. Ensure that service representatives have a complete, contextual view of the customer without the need for manual re-keying.
Appian customer story:
A global biopharmaceutical leader unified their anti-corruption compliance across 140 global markets with Appian AI. The solution automates high-risk healthcare professional (HCP) engagements by extracting data from unstructured agendas and emails to streamline engagement requests. This has slashed engagement contract execution from eight weeks to less than one day and reduced request initiation time by 88%.
The new standard for IDP
The transition from simple OCR extraction to end-to-end document automation marks the next frontier of enterprise efficiency. Treating document automation as a standalone extraction task is a strategic dead end. The real opportunity lies in turning document data into a dynamic catalyst for action within a unified, secure platform.
1 Lucarini, D., & Pelz-Sharpe, A., Market Momentum Index: Intelligent Document Processing (IDP) Survey 2025, Association for Intelligent Information Management (AIIM), 2025.
