In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the generative AI sophomore slump.

You will discover why so many businesses are stuck at the same level of AI adoption they were two years ago. You will learn how anchoring to initial perceptions and a lack of awareness about current AI capabilities limits your organization’s progress. You will understand the critical difference between basic AI exploration and scaling AI solutions for significant business outcomes. You will gain insights into how to articulate AI’s true value to stakeholders, focusing on real world benefits like speed, efficiency, and revenue. Tune in to see why your approach to AI may need an urgent update!

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Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn – 00:00
In this week’s In-Ear Insights, let’s talk about the sophomore slump. Katie, you were talking about the sophomore slump in regards to generative AI. I figured we could make this into a two-part series. So first, what is the sophomore slump?

Katie Robbert – 00:15
So I’m calling it the sophomore slump.

Basically, what I’m seeing is a trend of a lot of companies talking about, “We tried. We started implementing AI two years ago—generative AI to be specific—and we’re stalled out.”

We are at the same place we were two years ago. We’ve optimized some things. We’re using it to create content, maybe create some images, and that’s about it.

Everyone fired everyone. There’s no one here. It’s like a ghost town. The machines are just whirring away in the background.

And I’m calling it the sophomore slump because I’m seeing this pattern of companies, and it all seems to be—they’re all saying the same—two years ago.

Katie Robbert – 01:03
And two years ago is when generative AI really hit the mainstream market in terms of its availability to the masses, to all of us, versus someone, Chris, like you, who had been using it through IBM and other machine learning systems and homegrown systems.

So I bring it up because it’s interesting, because I guess there’s a lot to unpack here.

AI is this magic tool that’s gonna solve your problems and do all the things and make you dinner and clean your room.

I feel like there’s a lot of things wrong or a lot of things that are just not going right. A lot of companies are hitting this two-year mark, and they’re like, “What now? What happened? Am I better off? Not really.”

Katie Robbert – 02:00
I’m just paying for more stuff. So Chris, are you seeing this as well? Is