I went to the HumanX Conference last week and had a mildly unsettling realization:
I have no idea what half these people are talking about.
It started in the opening keynote. AI as a five-layer cake. One of the layers? Inference. Everyone around me nodded like this was Marketing 101, and I’m sitting there thinking… should I know this?
So I did the only sensible thing. I wandered the floor until I found a booth with “inference” in the headline and asked, “What is that, exactly?” (We’ll come back to that.)
Get Curious on Purpose
There’s something oddly powerful about putting yourself in a room where you don’t speak the language. It’s like traveling to a foreign country where you catch every third word and fill in the rest with context and guesswork. You can either pretend you get it… or you can get curious.
I chose curiosity.
I talked to vendors I wasn’t shopping. I stopped at booths because of tchotchkes I didn’t need. I ran into a couple of fellow Huddlers doing the exact same thing—wandering, absorbing, trying to make sense of it all. One random stop led to a company sitting on a goldmine of HR data that could be wildly useful to CMOs. I would never have found it if I stuck to my “agenda.”
And then there was the sea of sameness. AI-native, AI-driven, AI-powered, AI-everything. Different logos, same language, zero clarity.
Until Sentry’s booth broke through with a single line: “Someone’s gotta babysit the bots.” Finally, a problem I understand. A point of view I can remember. A reason to stop.
Sameness Is Your Opening
That’s when it hit me. If you’re a marketer walking a floor like this, the takeaway isn’t just about AI.
It’s about you.
Go where you don’t understand the language. Ask the question that makes you feel a little dumb, because chances are, you’re not the only one.
And when you see a hundred companies saying the same thing, that’s not a branding problem.
That’s your opportunity.
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FYI, Inference (in AI terms) is the moment when a trained model actually does something useful, like answering a question, generating content, or making a prediction. Don't ask me to go any deeper - as it was, I needed help from ChatGPT to craft this explanation!
Written by Drew Neisser
