Digital Velocity

Somebody on your team is uneasy about AI. You asked why, got an answer that sounded a little thin, and let it go. Sheryl Barbosa does not have that option. She is an environmental scientist and a sitting city council member, which means when a data center goes up outside of town, the neighbors bring her their fears. Her job is sorting the concerns that hold up from the ones that quietly stopped being true, and then talking to people about it without telling them they are wrong. In this conversation with Erik Martinez she covers what has actually changed about data centers, water, and power inside the last year, and why some of what all of us have been repeating is out of date. Then the episode turns. Erik could look up answers to the water question or the power question. But, there is no way to look up information about his own team, and he had been reading their AI hesitation as a verdict on the people rather than as the information it was. There is one question to ask your team, and how you frame it determines whether the answer that comes back is useful or worthless.

You've been using AI for months. You can see what it does. And when you look around the room, you can count on one hand the people on your team who are actually using it. The rest aren't pushing back. They just haven't started. "I had to hear from some other people how they're using it in their daily lives, and I didn't wanna just trust people who are tech-savvy." That's Mark Maynard, a coach, author, and speaker who helps leaders in hotels, restaurants, museums, and a construction company connect purpose to daily operations. Six months ago, he was the person on your team who still hasn't tried it. Using ChatGPT for recipes and road trip stops, nothing more. Mark joins host Erik Martinez on Episode 116 of the Digital Velocity Podcast to talk through what actually changed, and what it means for leaders trying to bring their teams along. Mark shares the specific moment a client problem broke through months of skepticism, explains why trusted people telling real stories mattered more than any demo, and describes how he used AI to help a construction company turn 1,000 pages of operational playbooks into something their employees would actually remember. "Efficiency was not the desired outcome, depth was." If the people on your team haven't bought in yet, this conversation reframes why, and what to do about it.

Tension-first. Functions as a trailer. The listener must hear the episode to get the answers. Jess Loseke spent 16 hours last weekend on her employee handbook. With AI. Your first question is probably the same as ours: why would that take 16 hours with AI? That is the wrong question. The right one is harder to sit with. "What is a pain to me are the things that are not getting done in my business because I cannot afford to hire for them. Those are the things that are killing the growth of my business right now." Jess Loseke, Co-founder, Midwest Barrel Company Jess co-founded Midwest Barrel Company, the first company to put a barrel (think Bourbon or Whiskey) on the internet. She runs lean, she's tech-forward, and she's ignoring the most common piece of AI advice right now. She's not starting with her most repetitive tasks. She's starting somewhere that, on the surface, sounds like the wrong place. Her business partner has a PhD. He's the best salesperson she's ever met. He sat down in a meeting and said, "I'm failing to see how I'm going to use this in sales." If a co-founder at an AI-forward company is saying that, what does it mean for the rest of us? Jess has an answer. It starts with a number: 75%. And it changes the math on what "good enough" means when the alternative is zero. This conversation with host Erik Martinez goes somewhere most AI conversations don't.

You are publishing more content than ever. So is everyone else. And somewhere in the rush to keep up, a lot of it started to sound the same. David Ebner, President of The Content Workshop, has a blunt explanation for why. "A tool doesn't know what good is." In this episode of the Digital Velocity Podcast, host Erik Martinez and David Ebner get into storytelling in the age of AI: why so much of it reads like word salad, what actually separates good from generic, and why the speed everyone is chasing might be the very thing making the work worse. David has spent 13 years telling brand stories, and he does not think AI is the problem. He thinks the problem is that most people never learned what good looks like before they handed the work to a machine. There is a specific thing David does before he ever hits the magic button that most people skip. Miss it and you get slop at volume. Get it right and the tool starts turning you into something closer to a superhuman writer. Listen to Episode 114 to hear where human creativity has to stay in the process, and why good was always good no matter how it gets made.

Erik Martinez and Pat Barry made their AI predictions six months ago. Agents, AI shopping, rising costs, governance. They were right about almost all of it, and almost none of it showed up the way they expected. Pat keeps running into the same pattern across every organization he works with. Someone has quietly built something remarkable with AI. When Pat tells them to share it, the answer is always some version of "yeah, they're not really into it." The capability exists. It's invisible. And nobody is asking why it stays that way. Meanwhile, Erik went from spending his days in Excel, PowerPoint, and Canva to doing ninety percent of his work inside tools that didn't exist in their current form six months ago. Pat's building entire training decks with agents that get him 85% of the way there in a quarter of the time. AI platforms are turning into the new office suite, and most people haven't realized the shift already happened. Token costs are climbing and Erik describes trying to track them as "absolutely maddening." One of Pat's healthcare clients made a governance decision that positioned them as what Pat calls "the team of the future." A university with 50,000 employees and access to the same tools can't keep up. The predictions were about what AI would do. What actually changed was how the humans work. That gap is the conversation in Episode 113.