How to Measure AI Adoption at Work | Bernard Meyer

Bernard Meyer (0:00)

AI, we still believe in it, but the way we're measuring it is wrong. So we switched to a outcome-based. So every single team, they had to focus on not what they're doing with AI, but why they're doing with AI and what outcome they're gonna achieve. So if we're doing outreach emails, they need to move the positive response rate from 1.5% to 3% with AI. We don't care what tools you're using, we don't care about the prompts. We're focused only on the outcome.

Brooke Gramer (0:24)

Welcome to the AI Movement Podcast, the space where modern entrepreneurs and founders come to stay current and navigate their next move with AI together. I cover the conferences, sit with the people leading this shift, and I bring it all here. Broken down, without the hype, whether you're building something, pivoting your work, or trying to keep ahead ethically, you are in the right place.

Let's get into it. Hello and welcome back. Today's guest, Bernard Meyer, did not take a traditional path into AI. He spent over a decade in marketing, then after teaching himself through hands-on experimentation, became OmniCen's first AI operations manager. In this conversation, Bernard takes us inside OmniCen's AI as a Habit Initiative and shares what it actually takes to make AI part of how an entire company works. We talk about where AI is producing real results across engineering, sales, and customer support, where it still falls short, and why every AI workflow needs to be tested before it goes live. His journey proves that you don't need a traditional engineering background to help shape how AI is used in your company. All right, let's dive into my conversation with Bernard. Bernard, it's so wonderful to have you on the AI Movement Podcast. Thank you so much for being here.

Bernard Meyer (1:46)

Well, thank you very much for uh inviting me. I am always excited to talk about AI. So please let me know when I'm talking too much.

Brooke Gramer (1:55)

Yes, I'm more excited because you also have a marketing background like myself. But for listeners who might not know you yet, could you share a little bit about yourself and how you ended up in the AI space now?

Bernard Meyer (2:08)

Oh yeah. So I have been working in marketing before this transition to AI for I would say maybe 14, 15 years. And the last position I had was the senior director of communications and creative. So pretty much, you know, branding, PR, video, social media, content, lots of creative stuff and design as well. But then I got, I mean, I had been getting into AI a lot over the last few years, you know, immediately when Chat GPT 3.5 came out and it took over the world. And then I just kept investing into it. And then I was pushing this the CEO of the company. I'm like, guys, we need to we need to do something because I feel like we're not we're not really pushing AI internally enough.

And so finally he just came to me with a proposition. He's like, okay, put your actions where your mouth is. Would you like to be the first AI operations person in this company? And I said, definitely. I didn't even hesitate.

So I made that switch last year in September.

Brooke Gramer (3:00)

So are you self-taught with AI, or did you go to school or upskill in any way?

Bernard Meyer (3:06)

Oh, completely self-taught. And the way I approach everything, I guess many of your listeners are probably the same. It's like you can do a lot of theoretical stuff, but really when you get your hands dirty and when you actually build and get into the details, that's when you learn the most. And so I tried my best to learn about ML and all that kind of stuff, but really I just wanted to see what AI can do. Um, and so the first thing I did, ChatGPT came out like in the beginning of November or something along those lines, and then immediately I decided I wanted to publish my first book completely written by ChatGPT, and it was a very painful process, but eventually I published it under a fake name on in Amazon, and you know, this that process of of seeing how much you can do with AI and how you have to at that early time, you know, Chat GPT didn't even have memory, right? So I had to figure out how to do all that and kind of make this whole book just a chat GPT. So I've been doing that kind of stuff, you know, sort of on my own time and and then pushing it internally as well, but completely self-taught, just pushing the boundaries. And I think it's probably the way that I would recommend most people to do it because the the problem with theoretical stuff is that by the time it's published or a video comes out or a lesson comes out, or certification comes out, oh my god, you're like six months behind and it's already moved far ahead. So I guess the best thing to do is just see something interesting, try it and learn.