AI Agents in Document Processing: The Future of Intelligent Workflow Automation

In the business technology sector, incremental improvements occur consistently. Our work methods today usually look at least slightly different from how they did only a few years ago. However, sometimes new innovations create opportunities to transform work significantly, delivering real, valuable change for businesses. The rise of AI agents is one such innovation, and agentic AI has had a significant influence on the current landscape of workflow automation.

With the ability to improve and extend existing automation, AI agents represent genuine potential. This is especially true in content-heavy workflows, especially document processing, a critical workflow in departments as wide-ranging as HR and legal to accounts payable and receivable. What makes agentic AI such a valuable opportunity, and how does it fit with other solutions? Let’s begin with some definitions.

What Are AI Agents? A Quick Explainer

Many people are familiar with today’s “large language models” (LLMs) that underpin the most popular and well-known artificial intelligence platforms today. “Agentic” AI leverages LLMs, too, but does more in a business environment than in the digital interactions typical of LLMs. Autonomous systems can review the output generated from a query or prompt and use that information to act independently. They accomplish business tasks that would typically require human intervention, such as analyzing large amounts of data or updating database records.

On its own, an LLM can’t directly interact with business systems. However, paired with an AI agent, the result is a powerful combination that can “reason” like a human to determine the best course of action and then execute that goal. Agentic solutions support automation journeys by opening the door to further streamlining of processes that may once have required a high degree of “hands-on” work. When paired with technology such as robotic process automation, agents can interact with these other tools to move processes closer to end-to-end automation.

Why AI and RPA Are Ideal for Document Processing Automation

Document-related processes have in the past required a substantial investment of manual labor. Documents must undergo data extraction, the data must be validated, and the information must be entered into the correct systems. Likewise, understanding the contents of a document takes time for humans. With AI agents and supporting systems, all these tasks become much simpler and faster. Even in high-volume environments, an agent can provide a clear answer about a document’s importance or context rapidly.

It can use robots to assist with extraction, then base its next move on the data it receives. For example, invoice information may need to be exported to various databases or ERP modules. With agentic AI, doing so can take place in a virtually touchless environment. The result: higher data quality and rapid access to the information your business needs to make decisions.

Exploring Solutions to Enhance Agentic AI Impacts

Let’s explore investments in agentic systems, a driver of value and results in your business. The Tungsten Marketplace is an online directory of solutions built by proven Tungsten partners and others to demonstrate techniques, support rapid automation deployment and more. One Marketplace solution in particular offers opportunities to investigate developing modern workflows powered by agents.

The Example Agent for Tungsten TotalAgility

Developing an agentic system might seem complex and time-consuming. However, this free solution from the Tungsten Automation Professional Services team provides the guidelines needed to understand how to move forward. Leveraging the power and flexibility of TotalAgility, you can use this project package as a template for building your first agent.

The goal of this template is straightforward: develop an AI task management or task planning agent. Properly configured, this agent can call upon other digital workers or even “micro-agents” that also use AI or RPA to accomplish tasks. The management agent provided in this template uses the typical, standard interfaces for data input and output from custom LLMs, so your agent does not need to understand specific details about the implementation of the sub-agents it calls on for other tasks.

Instead, a registry of available agents allows the managing agent to quickly assess their capabilities and make smarter decisions during the planning phase of how to resolve a user query or request. With this functionality, it is possible to use the agent as a top-level director of broader work processes, or you can set it up as a chat engine within a TotalAgility form. In this latter scenario, users can then interact with the agent via generative AI chat to control the agent and direct work tasks.

With the opportunity to structure automation for intensive processes that may require the support of other software robots or AI agents, you can bring simplicity and speed to efforts that otherwise might require intensive and error-prone manual work. Simultaneously, you also gain a flexible solution that you can change and modify as business requirements demand.

Consider How Intelligent Workflows Can Transform Your Business