In-Ear Insights: Getting Real Value from Generative AI

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss scaling Generative AI past basic prompting and achieving real business value. You will learn the strategic framework necessary to move beyond simple, one-off interactions with large language models. You will discover why focusing on your data quality, or “ingredients,” is more critical than finding the ultimate prompt formula. You will understand how connecting AI to your core business systems using agent technology will unlock massive time savings and efficiencies. You will gain insight into defining clear, measurable goals for AI projects using effective user stories and the 5P methodology. Stop treating AI like a chatbot intern and start building automated value—watch now to find out how! Watch the video here: Can’t see anything? Watch it on YouTube here . Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-getting-real-value-from-generative-ai.mp3 Download the MP3 audio here . Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] 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*. Another week, another gazillion posts on LinkedIn and various social networks about the ultimate ChatGPT prompt. OpenAI, of course, published its Prompt Blocks library of hundreds of mediocre prompts that are particularly unhelpful. And what we’re seeing in the AI industry is this: A lot of people are stuck and focused on how do I prompt ChatGPT to do this, that, or the other thing, when in reality that’s not where the value is. Today, let’s talk about where the value of generative AI actually is, because a lot of people still seem very stuck on the 101 basics. And there’s nothing wrong with that—that is totally great—but what comes after it? Christopher S. Penn – 00:47 So, Katie, from your perspective as someone who is not the propeller head in this company and is very representative of the business user who wants real results from this stuff and not just shiny objects, what do you see in the Generative AI space right now? And more important, what do you see it’s missing? Katie Robbert – 01:14 I see it’s missing any kind of strategy, to be quite honest. The way that people are using generative AI—and this is a broad stroke, it’s a generalization—is still very one-off. Let me go to ChatGPT to summarize these meeting notes. Let me go to Gemini to outline a blog post. There is nothing wrong with that, but it’s not a strategy; it’s one more tool in your stack. And so the big thing that I see missing is, what are we doing with this long term? Katie Robbert – 01:53 Where does it fit into the overall workflow and how is it actually becoming part of the team? How is it becoming integrated into the organization? So, people who are saying, “Well, we’re sitting down for

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