Leading Change

Anthropic Says We’re Losing Control of AI

Anthropic has issued another warning about artificial intelligence. But this time, the concern is not job displacement or productivity. It is the possibility that AI could soon begin improving itself. In this episode of Leading Change in the Wild, I break down Anthropic’s latest report on recursive self-improvement and what it means if AI reaches a point where it can build, test, and improve future versions of itself with minimal human involvement. But beyond the technology itself, this report raises some deeper questions. Who should be leading these conversations? And what happens when the companies warning us about the risks are also the companies building the technology? Here’s what I unpack: * What recursive self-improvement actually means * Why Anthropic believes we may be approaching a major AI inflection point * The challenge of keeping humans in control of increasingly capable systems * The “prisoner’s dilemma” at the center of AI development * Whether AI companies can simultaneously be the warning system and the builder * How regulation, competition, and incentives collide in the AI race * The connection between recursive AI, model collapse, and the dead internet theory The takeaway is not just about technology. It is about incentives, accountability, and who gets to shape the future of AI. Because if the people raising the alarm are also the people benefiting from the outcome, we need to ask harder questions about how these decisions are being made. 👇 Let’s discuss: * Should AI companies be leading conversations about AI regulation and ethics? * Are we approaching a point where AI can meaningfully improve itself? * Is a global pause realistic, or are we already too far down the path? 🔔 Subscribe for weekly insights on digital transformation, leadership, and emerging technologies.

AI CEOs Just Changed Their Story

For years, some of the biggest names in AI warned us that artificial intelligence would eliminate jobs, disrupt entire industries, and fundamentally reshape the workforce. Now, many of those same leaders are saying something very different. In this episode of Leading Change in the Wild, I break down the growing narrative shift coming from AI executives and why the people who once warned of mass job displacement are suddenly talking about productivity, augmentation, and the importance of human connection. So what changed? Here’s what I unpack: * The fear-based messaging that defined the early AI boom * Why AI leaders are changing their tone on job displacement * Sam Altman’s surprising comments about human interaction and AI * Dario Amodei’s shift from replacement to productivity multiplier * How IPO pressure, public sentiment, and adoption challenges may be influencing the narrative * Why human connection still matters in an increasingly automated world * The bigger leadership lessons hidden inside this messaging shift The takeaway is clear. When the narrative changes this dramatically, it is worth asking why.   Because whether AI becomes a replacement, an enhancement, or something in between, leaders need to think critically about the messages they are hearing and who benefits from them. This is not just a technology conversation. It is a leadership one. Because the future of work will not be shaped by technology alone. It will be shaped by the choices we make about how we use it. 👇 Let’s discuss: * Why do you think AI leaders are changing their message? * Was the original narrative wrong, or is this new one? * Is the truth somewhere in the middle? 🔔 Subscribe for weekly insights on digital transformation, leadership, and emerging technologies.

Why Gen Z Graduates Are Booing AI

College commencement speeches are supposed to inspire graduates about the future. Instead, many students are booing the moment AI gets mentioned. In this episode of Leading Change in the Wild, I break down the growing backlash against AI messaging at college graduations and why so many executives seem completely disconnected from how young people actually feel about the future of work. Because this is not just about AI. It is about the growing sentiment gap between leadership and everyone else. From viral commencement speeches to AI failures during graduation ceremonies themselves, we are watching a generation push back against the idea that an AI-dominated future is inevitable. Here’s what I unpack: * Why graduates are booing AI-focused commencement speeches * The growing disconnect between executives and young workers * How fear-based AI messaging is shaping Gen Z’s outlook on work * Why “adapt or get left behind” is failing as a leadership strategy * The contradiction in telling people they shape the future while also saying AI is inevitable * How AI hype is starting to overshadow human achievement and creativity * What leaders should be saying instead if they want real trust and adoption The takeaway is clear. People are not resisting technology. They are resisting the way it is being forced on them. This is not just a technology conversation. It is a leadership one. Because the future of AI will not be shaped by fear, mandates, or hype. It will be shaped by how well leaders can bring people into the conversation. 📄 Download the AI Strategy Gap report for deeper insights into the growing disconnect between leadership and employees. → https://mailchi.mp/roloffconsulting/aigap [https://mailchi.mp/roloffconsulting/aigap] 👇 Let’s discuss: Were the students justified in booing these speeches? Do executives understand how younger generations feel about AI? What should leaders be saying about AI instead? 🔔 Subscribe for weekly insights on digital transformation, leadership, and emerging technologies.

OpenAI and Anthropic Just Admitted AI Isn’t Magic

If AI is supposed to replace human productivity, why are OpenAI and Anthropic spending billions to build human-led services companies? In this episode of Leading Change in the Wild, I break down the back-to-back announcements from OpenAI and Anthropic to launch venture-backed consulting and implementation firms designed to help companies adopt AI. And hidden inside these announcements is a quiet admission. AI is not a magic wand. Because despite all the hype around instant productivity and “AI-first” transformation, companies are running into the same problem technology implementations have always faced. The people side of change. Here’s what I unpack: *  Why OpenAI and Anthropic are launching AI-focused services companies  *  The real reason enterprise AI adoption has been so difficult  *  How the “AI magic wand” narrative is colliding with reality  *  Why buying AI tools without strategy creates confusion and waste  *  The ongoing gap between technology implementation and true transformation  *  Why leadership, training, and communication matter more than ever  *  The danger of skipping over change management in the rush to adopt AI  The takeaway is clear. AI alone will not transform your business. Real transformation happens when technology, leadership, process, and people work together. This is not just a technology conversation. It is a leadership one. Because the companies that win with AI will not be the ones that adopt it the fastest. They will be the ones that adopt it with the most intention. 👇 Let’s discuss: *  What do these new AI services companies signal to you?  *  Is your organization focused more on technology or strategy?  *  Do you think most companies are prepared for the people side of AI adoption?  🔔 Subscribe for weekly insights on digital transformation, leadership, and emerging technologies.

Tokenmaxxing Is Breaking AI Strategy

Companies are racing to adopt AI. But what happens when they start incentivizing the wrong behavior? In this episode of Leading Change in the Wild, I break down the rise of “tokenmaxxing” and how AI leaderboards inside major companies are driving massive usage… without delivering real value.   From engineers burning tokens to hit leaderboards to companies blowing through millions in AI spend, we are starting to see the consequences of chasing usage instead of outcomes. Here’s what I unpack: *  What “tokenmaxxing” is and why it’s spreading across companies  *  How AI leaderboards are driving the wrong behaviors  *  The massive cost of AI usage without clear strategy  *  Why companies are burning through budgets faster than expected  *  The connection between AI spend and layoffs  *  What the data actually says about AI productivity gains  *  Why incentivizing usage instead of value is a leadership failure  The takeaway is clear. More AI usage does not equal more productivity. If you measure the wrong thing, you get the wrong outcome. This is not just a technology problem. It is a leadership problem. Because the way you incentivize behavior will determine whether AI becomes an advantage or a liability. 👇 Let’s discuss: *  Is your company tracking AI usage or actual outcomes?  *  Have you seen behavior like this inside your organization?  *  What should leaders be measuring instead?  🔔 Subscribe for weekly insights on digital transformation, leadership, and emerging technologies.