The term 'Agentic AI' is appearing more and more in tech publications and boardroom conversations. But what exactly does it mean? And why is it fundamentally different from the AI we've known until now?
From Reactive to Proactive
Traditional AI — like a chatbot or recommendation system — is reactive. You ask a question, you get an answer. Agentic AI is proactive: the system receives a goal and determines itself which steps are needed to achieve it.
The Four Characteristics of Agentic AI
- Autonomy: acts independently without human input at every step
- Tool use: can call external systems (APIs, databases, browsers, code execution)
- Planning: breaks complex goals into subtasks and executes them in a structured way
- Memory: remembers context across multiple sessions and adapts behavior based on experience
Agentic AI vs. Chatbot vs. RPA
A chatbot answers questions. RPA executes fixed scripts. Agentic AI does both and more: it responds to unexpected situations, adapts the approach, and works toward an end result — not a fixed sequence of steps.
Conclusion
Agentic AI represents a fundamental shift in how companies use automation. No longer just for fixed, predictable tasks — but for complex, adaptive processes that previously only humans could perform.
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