Imagine automating tasks that once required constant human intervention. That’s the power of agentic automation. This modern approach to business process automation uses AI agents to handle complex workflows, freeing up your team and boosting efficiency. Agentic automation is a way to streamline business processes by using intelligent software agents that can make decisions and complete tasks autonomously, just like a highly skilled virtual employee.
What exactly are AI agents?
An AI agent is a software program designed to perform tasks to achieve a specific goal, all without human intervention. AI agents are able to make decisions, complete tasks, and adapt and learn over time. Because of their autonomous nature, agents can work as extensions of a human workforce, working with, and on behalf of, employees.
The basic components of an AI agent
Similar to an employee who needs to learn how to do a particular job with the tools that are available to them, AI agents need a set of components that provide instructions to complete their assigned task successfully. These components typically include:
- Goal: The outcome or end result the agent is expected to accomplish. Goals can be simple, single-step tasks or can be more complex, spanning multiple different steps and decision point. Example: Process customer invoices received in the past 30 days.
- Logic: Information that can be used to achieve the goal. Agents often utilize Large Language Models (LLMs) to provide an understanding of how to get the work done, but logic can also be provided as a parameter or input when creating the agent. Example: Using an LLM to understand the format of an invoice.
- Tools: Information, systems, applications or any combination of these that can be used to help the agent do the work. Example: Access to NetSuite, the company’s accounting system.
- Communication: The communication channel that an agent will use to communicate with its human counterparts. This could be a chat, an email, or even a phone call. Example: Sending an email confirmation to the customer.
- Memory: Agents are able to learn and adapt over time by “remembering” interactions and outcomes from previous jobs they have completed. Example: Remembering past invoice processing details to avoid errors.
The differences between GenAI and AI agents
While both technologies utilize artificial intelligence, Generative AI is focused on creating something new based on prompts it receives from a human. GenAI does not act autonomously, and cannot make decisions or adapt to real-world context on the fly.
Conversely, AI agents are built for action. Once they have a goal to accomplish, agents work autonomously, deciding how to complete their jobs utilizing the tools and context they’ve been given.
How can AI agents be used in automation?
AI agents can be used as part of a workflow or process automation in many of the same ways a human worker may be involved.Agents can seamlessly integrate into your existing workflows, acting as intelligent team members who:
- Decide when a particular automation should be started
- Make a decision as part of an approval or review step
- Complete a task or interact with another application or system
What are examples of agentic automation?
Agentic automation can be used to automate almost any type of workflow or process because of its inherent flexibility and adaptability. Almost any task or activity you do on a regular basis can probably be automated with an agent. Do you regularly compile weekly sales pipeline reports and track pipeline performance? Agents can be used to automate the entire process. How about answering Level 1 support questions from customers? An agent can handle those questions and escalate to a Level 2 engineer if needed. What about invoice reconciliation? Agents can do that too!
The possibilities are vast. Here are some common examples of how agentic automation is being used today:
- Supplier / Vendor Onboarding
- Accounts Payable
- Incident Management
- IT Service Requests
- Software License Management
Common industry-specific examples are:
- Insurance Claims Processing
- Prior Authorization for Healthcare procedures
- Product Lifecycle Management
- Retail Inventory Management
- Pharmaceutical Quality Assurance
What are the benefits of agentic automation?
RPA and rules-based workflow have been providing automation-related benefits for years, but now, with AI agents, we’re going to see a whole new level of efficiency. Agentic automation brings a host of benefits including freeing up human resources to work on higher-value projects, reducing cycle times caused by time-consuming data analysis, and improving operational agility so you can reach to changing market and business trends in real-time.
Getting started with agentic automation
Now that you’ve learned what AI agents are and how agentic automation can benefit your business, you may be wondering how to get started. Conduct a workshop with your team to identify processes that could benefit from AI agents. Think about areas of the business that have already benefited from some automation as well as processes that have not yet been automated.
From there, identify a few areas where you can experiment. Expect to fine-tune your agents as you go. Start small and iterate.
There are many platforms and tools available to help you start building your own AI agents. To get started, you may want to focus on an agent creation tool that provides the best ease-of-use. But, the power of AI agents becomes exponential when you start thinking more broadly about agents working together to automate end-to-end processes. In that case, a vendor who provides easy agent creation as well as a platform for orchestrating multi-agent automations will set you up for the greatest agentic automation success.
Want to learn how Elementum can help you on your agentic automation journey? Contact Us for a personalized consultation.