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- [Instructor] Agent AI automates AI
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by making human decisions using the reasoning power of LLMs.
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Can you imagine what you would like to automate
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with agent AI in enterprise?
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Pick any industry of your choice.
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Write your ideas in a notepad.
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Don't worry about whether you have the data
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to build this agent AI.
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We are exploring ideas without any limits.
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To design agent AI to automate purposefully to help humans,
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the starting point in imagining use cases is always
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to think about why you want agent AI to do this work,
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and what are the benefits to people.
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Here are top three use cases in the industry,
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which lend itself to using agent AI.
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Let's talk about driving growth first.
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How do companies drive growth?
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They analyze customer data to develop insights
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to see where they can generate incremental revenues,
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where they can reduce cost, example customer churn,
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and where they can innovate.
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This innovation can be upsell of new products
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to the same customers
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or new innovative products
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targeting new customer segments.
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Now, can you imagine how you can build agent AI
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to help drive growth?
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Pause the video and write your ideas on a notepad.
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You can use your own industry as an example.
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We learned about how agent AI
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can help with customer segmentation
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in the marketing use case lesson.
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Agent AI can be used to analyze customer data
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and use the reasoning power of LLM
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to do data analysis and arrive at insights.
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This can be used for customer segmentation
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or personalization insights.
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A LLM can reason and can offer insights.
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It cannot take action.
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This is where tools come in.
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The agent AI can call upon tools as code snippets
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or full fledged tools to run, to drive action.
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Then it can look at results
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with a reasoning capability of LLM
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to decide if the actions helped
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or can make a decision to iterate the segment of customers
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or the personalization recommendations.
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