What Is An AI Agent?

Table of Contents

1. What is an AI Agent?
2. Understanding AI Agents vs. Workflows
3. Key Characteristics of AI Agents
4. Common Misconceptions and Reality
5. Where AI Agents Truly Excel
6. The Future of AI Agents in Business
7. Best Practices for Implementation

What is an AI Agent?

An AI agent is a computer program that can work on its own to complete tasks without someone constantly telling it what to do. AI agents work within specific domains with defined goals. IMO, it is best defined in the beginning of this Youtube video by Anthropic.

What They Do

• Gather information: Collect data from websites, user questions, or other software
• Make decisions: Figure out what to do with that information based on its programming
• Take action: Perform tasks like sending messages, organizing data, or finding answers
• Learn and improve: Get better at its job over time by learning from successes and mistakes

Examples You Might Recognize

• The chatbot that helps you on a website
• Software that suggests products you might like while shopping online
• Programs that automatically sort emails or schedule meetings
• Virtual assistants that can book appointments or answer questions

AI Agents can save time by handling routine tasks, working 24/7, and processing information much faster than humans could. They’re becoming increasingly common in business software to automate repetitive work and help employees focus on more important. For example, Enfra is an agentic software that helps automate key aspects of SEO execution for B2B/SaaS.

Understanding AI Agents vs. Workflows

AI agents and traditional workflows differ in how they automate tasks. Workflows follow a fixed, step-by-step process. AI agents, however, work more freely and can adjust their actions. They use Large Language Models (LLMs) to decide how many steps they need to solve a problem. This change comes from real-world use and better models. Imagine workflows as following a strict recipe, while agents change their methods based on the task.

Key Characteristics of AI Agents

AI agents solve problems in a flexible way. They don’t follow fixed steps. Instead, they use different tools until they find a solution. They decide on their own which steps to take and how many tries are needed. They need clear instructions and good resources to work well. Think of an agent as a problem solver that picks its own path.

Common Misconceptions and Reality

Many people think AI agents can handle everything, but they have limits. For example, booking a vacation with an AI agent can take as much time as doing it yourself. You still need to tell it all your preferences and needs. AI agents are not magical fixes for complex tasks. Right now in March 2025, industry and vendors are often overstating what AI agents can do, leading to unrealistic expectations.

Where AI Agents Truly Excel

AI agents handle small, repetitive tasks well, boosting productivity through automation. They excel in coding environments where unit tests can verify their work. While consumer applications get attention, the real value is in business process automation. These agents work best on specific, well-defined tasks, not broad problems. The key is finding time-saving tasks that, when automated, can scale across an organization.

The Future of AI Agents in Business

By 2027, AI agents will change how they businesses operate. Companies will adopt multi-agent systems, where agents work together, as seen in game simulations. These agents will automate repetitive tasks and improve productivity. Success depends on creating products that can adapt and grow with smarter models. This flexibility allows organizations to use more advanced AI as technology improves.