What are AI Agents?
8An AI agent is a software program or system designed to perceive its environment, make autonomous decisions, and take actions to achieve specific, predetermined goals.1 Think of it as an intelligent entity that can act independently on behalf of a user or another system.2
Key aspects and characteristics of AI agents include:
Perception: They gather information about their surroundings using sensors (like cameras in robots) or digital inputs (like user queries, data streams, APIs, or databases).3
Decision-Making & Reasoning: Using artificial intelligence, particularly often Large Language Models (LLMs) as their core “brain,” agents analyze the perceived information, reason, plan sequences of actions, and make decisions to best achieve their objectives.4 They can often handle complex, multi-step tasks.5
Action: Based on their decisions, agents interact with their environment using actuators (like robotic arms) or by executing actions within digital systems (like sending emails, accessing databases, using tools, or calling APIs).6
Autonomy: A defining feature is their ability to operate independently and make choices with minimal human intervention or supervision once a goal is set.7
Goal-Oriented: They are designed with specific objectives or tasks to accomplish.8 Their actions are driven by the aim of reaching these goals.9
Learning & Adaptation: Many AI agents can learn from their experiences, interactions, and feedback.10 They adapt their behavior and improve their performance over time, making them suitable for dynamic environments.11
Memory: Agents often possess memory capabilities (both short-term for immediate tasks and long-term for context and learning) to recall past interactions and information, improving contextual relevance and performance.12
Tool Use: Advanced agents can utilize various external tools, software, or APIs to gather information or perform actions beyond their inherent capabilities.13
How AI Agents Differ from Similar Concepts:
AI Assistants (like Siri/Alexa): While sometimes considered agents, assistants are typically less autonomous.14 They primarily react to user requests, provide information, and require user confirmation for most actions.15 Agents often have more proactivity and decision-making power.16
Chatbots: Traditional chatbots are often simpler, following predefined scripts or rules for conversation.17 AI agents, especially those powered by LLMs, have more advanced reasoning, planning, and autonomous action capabilities.18
LLMs (Large Language Models): LLMs like GPT or Gemini are often the core intelligence engine within an agent, providing language understanding and generation.19 However, an agent encompasses the entire system including perception, planning, memory, tool use, and autonomous action execution, not just the language model itself.20
Autonomous Agents: This term is often used interchangeably with AI agents but sometimes emphasizes a higher degree of independence, self-learning, and the ability to generate and manage sub-tasks proactively to meet a broader objective without continuous human guidance.21
Examples of AI Agent Applications:
Customer Service: Handling inquiries, processing refunds, automating support tasks.22
E-commerce: Providing personalized recommendations, dynamic pricing, tracking orders.23
Finance: Detecting fraud, assessing risk, performing algorithmic trading.24
Healthcare: Assisting with diagnostics, scheduling appointments, providing patient reminders.25
Robotics: Autonomous vehicles, manufacturing automation, warehouse logistics.
Personal Productivity: Managing calendars, filtering emails, summarizing documents, automating research tasks (e.g., OtterPilot for meetings).26
Smart Home: Adaptive thermostats, intelligent security systems.27
In essence, AI agents represent a step towards more capable and independent AI systems that can proactively work towards goals in complex environments.28