Brianna White

Staff member
Jul 30, 2019
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Should you use A.I. in your business?

And if so, how?

Maybe you've quickly become a generative A.I. expert. Or maybe you've been playing around with GPTs and know enough to be dangerous. Or maybe you have no idea what all the fuss is about but it seems dystopian.

Either way, we're all acutely aware that the A.I. bandwagon is running out of room.

It's time to hop on.


Look, no one can give you the exact right answer, but I'll give you a framework to answer it for yourself.

First, Let's Ask the Right Question​

The part of A.I. that makes all the money is not so much about getting the right answer as it is about asking the right question.

So let's make sure we do that here too.

This new flavor of A.I. (and it is indeed just a flavor, is not the kind that's going to kill us all, yet) isn't all that new.

In 2010 and 2011, I co-invented the first commercially available natural language generation (NLG) engine and platform at Automated Insights, which is a fancy way to say that we taught computers how to write articles based on data.

While we used both A.I. and machine learning (ML) to enhance the engine and the platform, our product was neither pure A.I. nor pure ML. Since those early days, NLG has been combined with natural language processing (NLP), a science that started going mainstream with Alexa and Siri, and has now evolved to become generative A.I. -- what we think of as OpenAI and ChatGPT and the like.

But back in 2010, the term NLG hadn't been coined yet, or at least it wasn't mainstream enough to get on into our consciousness, so we referred to what we were doing as automated content, because automation is like 90 percent of what makes A.I. seem like magic and money.

So the real question you should be asking is, "How much automation should I use in my business?"

And to get to that answer, we have to understand the difference.

Thinking Versus Acting​

Machine learning is "thinking" and automation is "acting." As technology continues to blur the lines between machine learning (thinking) and automation (acting), we roll it all into one smart technology called A.I.

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Think of a self-driving vehicle. The ML tells it where to go, the automation executes those decisions. Those technologies are unrelated and usually self-contained, but they have to work in complete harmony.