From the course: Understanding Generative AI in Cloud Computing: Services and Use Cases

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Where agentic AI is a fit, and not

Where agentic AI is a fit, and not

From the course: Understanding Generative AI in Cloud Computing: Services and Use Cases

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Where agentic AI is a fit, and not

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- [Narrator] Agentic AI is a fit for scenarios where autonomy and decision making are required. Typical applications include automated complex workflows, virtual assistance, dynamic process optimization, and task benefiting from continuous learning and adaptation. These settings require AI to act without constant human oversight. Agentic AI excels in environments where rules and desired outcomes can be clearly defined, but the path to success may change such as supply chain management, personalized recommendations, or cloud resource orchestration. Here, it's the ability to monitor, decide, and adjust actions, brings efficiency and agility. High volume, repetitive operations like customer support bots, monitoring large IT environments or fraud detection are good fits. Agentic AI rapidly responds to changing patterns, scaling decisions beyond what human operators can handle, and adapting to new challenges as they arise. However, Agentic AI is not a good fit when problems are poorly…

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