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<v ->This is really the moment when generative AI is popping,</v>

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because finally, it's allowing enterprises

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to capture the value from AI

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without having access to armies of data scientists,

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which are a scarce talent.

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It's allowing enterprises to use their domain knowledge

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to query these generative AI models,

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and get value generating results out of them.

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It's proving to be a great equalizer

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because of the API development talent

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that's required to gain value out of it

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is quite easily available,

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so now everyone can have access to it and generate values.

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It's a very exciting moment in AI.

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I think there are really three things

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that enterprises needed to do

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to be able to take advantage of this technology

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for their businesses.

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Number one is, there's a very thoughtful selection

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of the actual business use cases

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that can derive benefit for the business

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and take advantage of the specific trove of enterprise data.

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Part two is picking the right platform

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to power the enterprise journey.

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The generative AI platform

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needs to be enterprise-grade from day one.

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This means it needs to be allowed for privacy,

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for security, for ease of use,

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for scalability, and so on and so forth.

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This is still an emerging and dynamic space

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and we expect new offerings to come up.

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And so keeping an eye on these

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and being able to evaluate those offerings

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to pick a true enterprise-grade platform

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will make a huge difference.

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And third will be to establish

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a very sound responsible AI framework within the enterprise

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to guide the development of the use cases,

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and make sure that issues like governance,

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liability, trustworthiness,

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and belief in the results of generative AI

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can be trusted upon

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to be able to drive enterprise results.