AI agents are software programs developed to perform specific tasks by processing information inputs. They make decisions based on data, rules, or learned behavior.
How AI Agents Work
AI agents function through three key components:
- Perception: They collect data from their environment using sensors, APIs, or other inputs.
- Decision-Making: They analyze the data, applying logic, machine learning, or predefined rules.
- Action: They execute tasks, interacting with systems, software, or users.
Examples of AI Agents
AI agents are everywhere. Some common examples include:
- Chatbots: Virtual assistants like HubSpot’s ChatSpot automate customer support and sales interactions.
- Recommendation Systems: AI agents in e-commerce suggest products based on user behavior.
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Go-to-market (GTM) agents: AI agents meant to streamline sales, marketing, and RevOps by automating key tasks like lead qualification, pipeline forecasting, and deal management. GTM agents act on real-time data to improve conversion rates, speed up decision-making, and drive revenue growth with minimal manual effort.
AI Agents vs. Large Language Models (LLMs)
AI agents and large language models (LLMs) are related but not the same:
- LLMs (e.g., ChatGPT, Claude, Gemini): These models process and generate human-like text based on vast amounts of training data. They excel at understanding and producing language but primarily operate as conversational tools rather than autonomous actors.
- AI Agents: These go beyond text generation to execute specific tasks. They can integrate LLMs as a component but also take independent actions based on context. AI agents interact with multiple data sources, make decisions, and execute real-world tasks, such as scheduling meetings, automating workflows, or controlling robotic systems. While LLMs provide intelligence, AI agents provide action.
Other AI Forms vs. AI Agents
- Traditional AI: Focuses on pattern recognition and predictions, like fraud detection in banking.
- Generative AI: Produces new content, such as text, images, or code.
- AI Agents: Go beyond prediction and generation—they take action.
Why AI Agents Matter
AI agents improve efficiency, automate tasks, and enhance decision-making across industries. As AI evolves, these agents will become even more advanced, integrating deeper into daily operations.
AI agents are already an integral part of many business workflows. As AI capabilities continue to develop, you're likely to see more AI Agents in your tech stack and work place. Understanding their capabilities, use-cases, and limitations can help you implement more efficient and effective business solutions.