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Agentic AI vs AI Automation: What’s the Real Difference?
TL;DR
Agentic AI, often confused with AI automation, involves creating intelligent agents that can adapt and respond to unexpected inputs, unlike traditional automation that follows predefined rules. The article highlights the challenges faced when deploying these systems in production environments.
✦ Why It Matters
Evaluate your AI systems for adaptability to unexpected inputs before deploying them in production.
Key Takeaways
- Differentiate between automation and agentic AI for better system design.
- Use automation for predictable, structured tasks.
- Implement agentic AI for tasks requiring adaptability and planning.
- Avoid mislabeling automation as agentic AI to prevent production failures.
How It Works
Agentic AI operates by defining a goal and dynamically selecting actions based on context and previous outcomes. For instance, a research agent assesses its findings to determine whether to search for more information or summarize results, showcasing its ability to adapt and plan.