Implementing GenAI at scale in the enterprise is like teenage sex

Everyone talks about it, nobody really knows how to do it

Everyone talks about it, nobody really knows how to do it, and everyone thinks everyone else is doing it, so everyone claims they are doing it...

hat was a quote from Cassie Kozyrkov, CEO of Data Scientific and former chief decision scientist at Google.

Her point?

Everyone's dropping the 'GenAI' buzzword in their conversations and posts.

But how many really get it?

I include myself in this.

I'm at the stage 1 year since OpenAI launched ChatGPT of test and play.

I am not an expert.

I am trying things out but not launching things till I understand what works and what needs work.

Lots of people right now are trying out things like building their own custom GPT.

I counted no less than 7 in my feed launched yesterday (Sunday 12th Nov).

There's nothing wrong with testing, don't get me wrong, but the 'we're doing it' echo gets louder every day.

The question is, who is 'doing it' right?

GenAI is not a magic wand but a tool.

It's not about 'having' it, but why and how you use it.

'How' you integrate it into your system that matters.

For instance, consider the company that uses GenAI for its data analysis.

The key isn't just implementing GenAI, but coupling it with their existing data framework.

The idea? Can they make it easier to unlock insights that were previously invisible?

Can someone with no experience login ask their business question and be shown the answer by GenAI?

Otherwise, what's the point? You're just adding a layer of complexity to the tool you created.

The takeaway is simple: Focus on 'why' and 'how' more than the 'what'.

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