Rethinking Document Automation: Why the Future Belongs to Agentic Systems

The convergence of Intelligent Document Processing (IDP) and AI agents is unlocking a new era of automation for enterprises. This powerful combination goes beyond data extraction, enabling systems to make cognitive decisions based on document content.

Yet many organizations still struggle to choose the right IDP solution. Whether it’s navigating outdated legacy tools, relying on underperforming products, or debating whether to build or buy, these challenges often lead to poor outcomes and stalled projects.

Turning documents into action is easier than you might think — and it doesn’t require investing in monolithic document AI solutions, or trying to build a solution using various AI tools and services.

Below we’ll explore how AI agents are redefining what document automation means, how it works — including data accuracy, document complexity, and integration — and hopefully put the nagging buy versus build debate to bed by highlighting some exciting customer outcomes.

Document automation in the Agentic Era

In the Agentic Era, AI agents are joining with IDP to power faster decision making as part of document workflows. Data that is intelligently extracted using ML models or generative AI is sent to AI agents that use an understanding of the content and reasoning to validate and reconcile data, and make decisions.

This kind of automation is transforming document processing by replacing rigid, rule-based legacy capture systems with flexible, learning-based Gen AI extraction models. The results are document agents that achieve over 95% accuracy and are fully auditable, making them ideal for industries with strict compliance requirements. This is what Automation Anywhere’s Document Automation offers.

Why use intelligent document processing with AI agents?

IDP turns messy, unstructured data into actionable information. This is a critical first step in the majority of business processes that rely on data trapped in documents to make decisions.

AI agents take this further: They can analyze the information that comes from a set of documents, make decisions, and take action like a human would, performing advanced cognitive tasks including reasoning as well as seamlessly handing off exceptions to humans with full context.

How does this work? AI agents analyze information extracted from documents to find patterns and insights, which helps them decide what actions to take. Based on this analysis, they choose the best course of action and can handle tasks like sending emails, updating records, detecting fraud, filing claims appeal, or interacting with customers — often at the same time.

As they work, AI agents build ongoing context memory that feeds back into their reasoning and execution abilities.

Gen AI delivers great accuracy and is constantly learning

Within the Agentic Process Automation System, AI agents handle document processing autonomously and intelligently. Generative AI for extraction is powered by Automation Anywhere’s Process Reasoning Engine (PRE), which delivers over 95% accuracy for any type of document and is trained on more than 400 million real-world documents and data to understand how business decisions unfold across complex systems. PRE powers more than 1,500 live deployments and more than 1 million AI agent executions across finance, healthcare, and more.

Document Automation also supports multimodality, combining the power of LLMs with Visual Language Models (VLMs), given that text alone doesn’t always tell the whole story. Visual elements like layout, tables, handwriting, and stamps often carry vital meaning, and by merging visual and textual understanding, we unlock document intelligence that purely text-based models can’t provide.

What document agents are achieving for customers

Our customers’ real-world experiences demonstrate how quickly and dramatically document agents make a difference. 

Jemena, for instance, has greatly reduced invoice duplications and can now process parked invoices from its 3,300 vendors on the same day. Meanwhile, Oscaic, a leading broker-dealer serving 11,000 financial professionals, saves 25,000 hours annually by automating its Automated Clearing House (ACH) transaction process.

Automation Anywhere customers leverage Document Automation in more than 150 different languages, supported by Generative AI. That means you can deploy IDP across regions and languages, whether for customer onboarding, healthcare claims processing, finance and accounting, or any other industry use case.

And across the board, customers have made it clear that Automation Anywhere is leading the way in IDP. That’s why we’re honored to be named a Customers’ Choice in Gartner’s Voice of the Customer Report for IDP solutions.

What’s the difference between IDP and OCR?

While optical character recognition (OCR) is a part of IDP, OCR only focuses on converting images of text into actual readable text data.

IDP, on the other hand, covers a wider range of capabilities that enable Document Automation. It uses vision models to understand document structure, employs native machine learning and pre-built models for data extraction, leverages Gen AI for extracting data from complex unstructured documents, and allows users to bring their own LLM models for specialized document workflows.

This makes deploying agentic Document Automation easy. Pre-trained models and Gen AI for extraction remove the need for complex and lengthy ML model training that demands deep technical resources.

And because Document Automation is part of the Agentic Process Automation System that already provides robust APIs, bots, SDKs, and connectors, deep document-processing capabilities — such as data extraction, classification, and validation — can be seamlessly embedded directly into line of business workflows and applications.

This also extends to the human-in-the-loop experience. Combining Document Automation with Automation Co-Pilot provides embedded contextual document review for business users and allows users to interact with other AI agents as part of a document review process, preparing data for downstream work that other AI agents would perform. This integration removes the need for separate review tools, reduces hand-offs, and speeds decision-making by keeping work in one seamless flow.

Getting started

The future of document automation is happening now with agentic systems that not only process data but turn it into action — driving speed, accuracy, and strategic value across the enterprise.

To get started, watch our on-demand webinar or connect with us for a meeting and demo.