How to Scale an AI-First Culture, and the CTO’s Role

Speaker A: Couple of days ago, I was sitting on the floor of my daughter's room with my coffee, watching her face plant into the yoga mat for the 14th time in a row. She's just three months old, she's learning to crawl. And I could see there was zero frustration. She was belly down, arms out and back into the mat again and again. I had this thought I couldn't shake my three month old daughter. Able to learn better than most Fortune 500 companies. And I don't mean that as a cute metaphor. I mean it structurally. And as a behavioral economist by education, I studied economics at Bocconi University in Italy. I can't help thinking that the way that a baby learns to crawl is the best way to think about behavioral change. And since cultural change in organizations is nothing more than collective behavioral change, crawling as an act contains every single principle an organization needs to adopt a new culture, and in this case, an, uh, AI first culture. You know what? Nobody tells you that babies don't learn to crawl because someone teaches them. You actually create three conditions and the crawling emerges on its own. And that word, conditions is the one that 95% of companies, according to an MIT Media Lab report, are getting wrong right now in their AI transformation journey. Here's your host, Andrea Iorio, speaking. I'm an Italian keynote speaker and USA Today bestselling author. As the former head of Tinder in Latin America for five years, Chief Digital Officer at l' Oreal Brazil, MBA professor at Fundasono Cabral, and now columnist at the MIT Technology Review. My latest book is between youn and AI, published by Wiley. You can get to know everything about my work@Andreiadio.com and today we're going to talk about why AI first is a crawling problem and not a tech problem. Stay with me. And so let's start with the baby. In developmental science, crawling is not really a motor skill. It's an emergent behavior. A motor skill is something you train and teach. An emergent behavior appears when the right conditions exist. What are the conditions? In this case, there's three first, tummy time. You have to put the baby belly down. It's uncomfortable, but that discomfort activates exactly the muscles the baby needs. Second, you let her fail. She falls 14 times like my daughter. And nobody files an incident report. The cost of failure is zero. And third, you place a toy there, just out of reach, but so that she has a reason to try. Now pause here for a second because a study by Ying Bao and colleagues presented at the Hawaii International Conference on System Sciences, investigated What makes people trust AI during collaboration? And what they found maps almost perfectly onto the baby. Two dimensions. The first one is cognitive perception. Is the tool easy to use? Is the coordination cost low? And second, emotional perception. Do I feel comfortable using AI? Do I enjoy it? So tummy time in the case of babies reduces cognitive complexity. Letting her feel reduces coordination costs. And the toy is emotional comfort and enjoyment. Three human conditions. And most companies have zero of the three. And what are the companies that are winning with AI doing? Well, they redesigned four things in particular. Four conditions. Not their tech stack, but four dimensions of how the organization thinks, builds, serves and grows. I call them the four floors because you can't crawl on a broken floor. And I summed it all up in my book between youn and AI. The first floor is data. You need data in order for AI to turn your business from reactive to predictive. An example is Mayo Clinic. Mayo Clinic is number one in CB Insights, AI Readiness index for hospitals. They don't just focus on treating diseases, they prevent them. And so are your dashboards and your data just a rear view mirror or they help you drive looking in front of you. The floor two is design. Design in order to turn your company's tools from automation to augmentation. See, nubank is the, uh, biggest fintech in Latin America. And they didn't replace their human agents with chatbots like most banks did. They built an AI powered panel that makes those humans better, providing real time, context, sentiment, analysis, suggested next action. That's not just automation, that's augmentation. And it's a design choice, not a tech choice. Floor three is pivoting away from transactions to generating value through experiences. Look at John Deere. For 197 years it was a tractor company. Today they sell intelligence to the farmer. The tractor is the same, but the value proposition is completely different. Stock went up over 500% since the beginning of the pandemic as a consequence of that. And floor four is people pivoting away from a, uh, hyper focus on hard skills to soft skills. See, AI ethicist Scott Aronson said something that would keep every professional awake at night. He said for any task with an objective measure of success, it's just a matter of time before AI outperforms the best humans. Um, what survives, what's not measurable? Judgment, empathy, ethical reasoning, the ability to sit in ambiguity and still decide. Four floors, Data, design, value, people. None of them are tech problems. Every single one of them is a leadership problem, a design problem, and even a trust problem. And here's where this episode makes me lose sleep because you see Deloitte's Trust ID Workforce Index found that senior leaders are 40% more likely to use unapproved AI tools from their own staff. In the tech sector, shadow AI usage hits 58%. The people who are supposed to be leading the transformation are the ones bypassing the system the most. But it even gets worse. According to the same report, employees trust in companies provided generative AI fell 31% in just three months in 2025, and trust in agentic AI systems that act autonomously dropped 89%. And Amelia Dunlop, CXO at Deloitte Digital, stated that workers see their employer as to two times less empathetic after AI is introduced into the workplace. Yes, we're deploying AI faster than ever, but people trust it less than ever. So what's the CTOS or CIO's role into all this? It's fourfold. One role for each floor. The first one is data. How you turn into an architect of the data foundation. You decide whether your organization's data is AI ready or AI hostile. Clean, centralized govern. Data is super important. It's boring work, I know, but it's the difference between scaling AI and scaling pilot project. Second design. You become an ecosystem designer. Your job isn't to build every tool, it's to build the ecosystem in which tools get deployed and governed. You know, teams start vibocoding. You need governance for that. You need an approved model stack, tiered risk classification. How many of you have a published policy on what marketing can build with AI? Uh, exactly. That's the gap. Third value. You become a strategic partner of business areas. And this one's uncomfortable because for the cto, it means leaving the server room and sitting into the business room. The hard truth is that the CTO who can draw a line from a model deployment to a revenue number keeps the budget. The one who can't becomes a cost center. And we know that cost centers get cut. And fourth people. The CTO becomes the champion of human readiness. And here, where the baby analogy comes back, remember the three conditions? Tummy time, permission to fail, and a toy. Well, that's your job, not HRs. It's yours because you're the one who understands what AI can do, what it can't, and what it needs from humans. See, McKinsey found that companies where senior leaders actively role model AI use are three times more likely to be high performance. Three times because of behavior, not because of technology. So you have four floors, four roles. Architect, designer, partner, and champion. And in none of them is the cto, the person who builds the AI. Uh, in every one of them, the CTO is the person who builds the conditions for AI to work conditions and not code, just like a parent builds the conditions for a baby to crawl. So being AI first is not just about tech strategy. It's not about models, it's not about computing power. It's not even about data, because data matters enormously. AI uh first is a crawling problem. It requires discomfort redesigning workflows, not bolting AI on top. It requires permission to fail, and it requires a reason to move. And above all, it requires trust. Not the kind you declare in an email, the kind you earn through decisions that cost you. See, my daughter will learn to crawl. She doesn't need a strategy deck. She needs these three conditions. Your organization is no different, and they're waiting to see whether you'll create these conditions or just send another email about AI uh. So these are some of the reflections that I wanted to spark. And as a homework, please think about what in reality are these conditions for you and your business? And so with this, I want to thank you for your attention and see you next week with another episode of between youn and AI.