Agentic Automation and IDP: Building Trust and Precision into Business Workflows

Tech companies are doubling down on AI’s capability to make decisions. Giant brands like Microsoft and Meta have committed millions of dollars to crafting the technology. Startups are raising millions more to get into the market.

And it’s all because of a new wave in automation driven by advancements in artificial intelligence: agentic automation.

Agentic automation is AI that doesn’t just assist but makes choices and takes actions independently. When agentic automation is combined with intelligent document processing (IDP), for example, businesses can not only extract important data but decide what to do with the information and put it to work—all automatically. Let’s take a look at how these combined technologies work together to change the way businesses tackle complex business workflows.

What is agentic automation?

Agentic automation refers to the use of intelligent agents (software or systems) to automate tasks by combining multiple technologies—such as AI, machine learning, decision-making processes, and automation tools—to carry out tasks autonomously. The key idea is that these systems can take actions based on specific inputs, learn from experience, and improve over time without needing human intervention for every step.

Basically, these AI systems are designed to make choices, take action, and solve problems on their own. Unlike traditional automation that follows predefined rules and workflows, agentic automation can adapt to changing conditions and handle dynamic, unpredictable tasks autonomously.

Take the insurance claims processing workflow, for example. When a customer submits a claim, traditional automation would extract key information from the document for a human insurance agent, who would then pick up the workflow and use that data to make decisions.

Agentic AI goes a step further. After extracting the data, it analyzes the information autonomously and makes decisions based on predefined rules or learned patterns. For example, the agentic AI might double-check an insurance claim, automatically approve it, and calculate the payout—without needing human intervention.

Of course, humans would still need to manage complex cases, but the agentic AI would handle the bulk of the decision-making and manage tasks end-to-end. Employees would then be freed up from rote decision-making to focus on more interesting challenges.

Common applications for agentic automation

Agentic AI has the potential to reshape almost every business process, including basic functions such as scheduling and document management. But let’s first look at how agentic AI can be used in specific industries:

• Insurance: Agentic automation can streamline claims processing by autonomously analyzing submitted claims, extracting relevant data, and validating coverage. Straightforward claims are handled entirely by AI with the ability to approve payouts on its own.
• Healthcare: Tasks like patient triage can be streamlined by agentic automation that autonomously reviews each patient’s symptoms, studies their medical histories, then prioritizes cases based on urgency.
• Banking: Agentic automation can be used for fraud detection, risk assessment, and transaction monitoring. It can also make faster lending decisions by analyzing a customer's financial history—while reducing human bias to boot.
• Government: Processing applications, verifying applications, flagging discrepancies—and even issuing approvals or denials—can be done by agentic AI to speed public services like benefits processing and tax assessments.
• Customer experience: Agentic AI can not only provide basic information but also actively make decisions on common customer service issues, such as choosing to issue a refund or prioritizing requests and inquiries.

How agentic automation and IDP complement each other

Since up to 80% of business processes are driven by documents, combining agentic automation with intelligent document processing (IDP) can dramatically improve how business gets done.

Put simply, agentic AI adds decision-making abilities that are powered by the accurate data extraction completed by intelligent document processing. First, IDP automatically extracts and structures data from invoices, contracts, medical records, and other documents using AI techniques like optical character recognition (OCR) and natural language processing (NLP). The resulting data is accurate, high-quality, and ready for analysis. Then agentic automation steps in to autonomously make decisions and take action.

IDP empowers agentic AI to perform at its highest capacity. By providing reliable, robust, and trustworthy data, IDP enables agentic AI to make the best decisions for seamless end-to-end workflows.