Getting real: The power of credibility in the AI world
By Peggy Tierney Galvin, co-founder, chief strategy officer
Recently, a friend in my book club texted the group chat a link to a piece from Variety magazine titled “Netflix Launches Hub Featuring ‘Bridgerton,’ More Book-to-Screen Adaptations Targeting Nine Reader Types.” The Bridgerton fanatics in the chat immediately began to discuss, but dear reader, the article got me thinking about enterprise sales.
Mining IP ad infinitum for content spinoffs is everywhere: the Mouse Empire is grimly invading every planet in the galaxy, no matter how far, far away, for new streaming ideas. A friend once told me that after the birth of his youngest child that one of his biggest worries as a new father was whether to introduce his children to the Marvel Cinematic Universe in order as released in theaters or on TV, or in the chronological order of the timeline. I still don’t know if he’s figured it out. Given that there are 37 movies and 30 shows in the MCU to get through, his kids might be in college by then.
And now AI is moving in on the content game. When we open up our Netflix feed, we’re greeted (confronted?) by a wealth of movies and shows, all sorted according to your interests as informed by your viewing habits. AI in entertainment is still nascent, but it’s coming. Even Martin Scorscese seems improbably sanguine about it. But over here in enterprise tech, we’ve seen the impact AI has on content development and output for a few cycles now, and we’re wrestling with some uneasy observations.
This is how it works. We read a hot take on LinkedIn. It seems insightful, and pithy. It has some stats that raise your eyebrows and make you think, “huh, that’s interesting.” But you know the post’s written by AI from a prompt. So you’re already less impressed by that person’s knowledge than you might have been four years ago, for example, with the expectation that the insight in the post came from the person who posted it, because they wrote it. Now, you can reasonably assume that the content and the message is important to them, but you know you’d need more before you could assume that their own level of expertise and experience matches what an LLM can produce.
And in most cases, it’s fine! Using AI tools for analyzing meeting recordings for takeaways and action items, for example, is a great help. And further up the abstraction stack, we’re seeing new job roles like “internal forward deployed engineers” who design teams of AI agents to deploy at enterprise workflows using enterprise data… and also using their uniquely subtle human understanding of the best way to do that. But what about the middle-of-the-road cases, for “nontechnical” marketers who are looking for the best way to take advantage of these great new tools, but also realize the giant deluge of content it’s cascading over our targeted audiences, who are just as glazed over and overwhelmed as we are, clicking through option after option?
There’s a reason why authenticity is so important these days. And that’s the same for marketers looking to make a real connection with prospects. The more you can be real, the better. And being real to your customers means showing them real people, real stories, realsamples of your work, with real examples and real outcomes. Connect your expertise and your technology’s business benefits back, over and over, to actual, specific examples that illustrate the problem and illuminate the solution.
There’s a way to do it right. And we can help you do it.
