6 Types of AI Agents and What Each One Does Best

AI agents, which are software systems that perceive, decide, and act toward human-defined goals, are categorized into six types based on their decision-making behavior: simple reflex, model-based reflex, goal-based, utility-based, multi-agent systems, and learning-augmented agents. Each type has distinct strengths and limitations, such as simple reflex agents operating on fixed rules without memory, and learning-augmented agents improving decisions over time through feedback. These agents differ from other AI implementations like chatbots and rule-based automation, as they offer bounded autonomy, where human-defined objectives and guardrails guide their actions. Sigma's platform integrates these AI agents with live cloud data warehouses, allowing them to operate under permissions and governance models, which ensures data security and compliance while offering business users flexibility and IT control. Sigma facilitates interaction with these agents through a user-friendly interface, enabling various workflows, from conversational queries to fully autonomous tasks, transforming how business teams leverage data for decision-making.

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