Leading Change

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.

The AI Strategy Gap

There’s a growing gap in how AI is being experienced inside organizations. And most leaders are missing it. In this episode of Leading Change in the Wild, I share original research from her audience that reveals a major disconnect between leadership and employees when it comes to AI adoption. Because while leaders are optimistic, employees are overwhelmed. And that gap is creating more problems than progress. This is not just about AI. It is about how we lead change. Here’s what I unpack: *  The stark difference between leadership and employee sentiment toward AI  *  Why most companies don’t actually have an AI strategy  *  How hype and external pressure are driving decision-making  *  The reality of AI creating more work instead of less  *  Why poor training and unclear direction are hurting adoption  *  The “FOMO cycle” and how it keeps repeating  *  What leaders need to do differently to close the gap  The takeaway is clear. This is not a technology problem. It is a leadership problem. If you want real results from AI, you have to start with the problem, not the tool. And you have to bring your people into the process. Because without alignment, strategy is just noise. 📄 Download the full report here: https://mailchi.mp/roloffconsulting/aigap [https://mailchi.mp/roloffconsulting/aigap] 👇 Let’s discuss: *  Does this gap exist in your organization?  *  Is AI making your work easier or more complicated?  *  What would need to change for AI to actually deliver value?  🔔 Subscribe for weekly insights on digital transformation, leadership, and emerging technologies.

Gen Z Is Sabotaging AI… But Here’s Why

44% of Gen Z workers say they’ve tried to “sabotage” AI at work. But before we jump to conclusions, we need to ask a better question. Why? In this episode of Leading Change in the Wild, I break down the latest data on Gen Z’s shifting sentiment toward AI and why this reaction has less to do with resistance to technology and more to do with how it’s being introduced. Because this is not a story about a generation rejecting AI. It is a story about what happens when leadership gets the rollout wrong. From fear-based messaging to “AI-first” mandates, we are watching a growing disconnect between how companies are deploying AI and how employees are experiencing it. Here’s what I unpack: *  The data behind Gen Z’s declining trust and rising anxiety around AI  *  What “AI sabotage” actually looks like in the workplace  *  Why poor rollout strategies are driving risky and reactive behavior  *  The impact of fear-based narratives around job loss and automation  *  How AI adoption is increasing workload, not reducing it  *  The tension between productivity expectations and work-life balance  *  Why Gen Z’s pushback may actually be a signal leaders need to listen to  The takeaway is clear. This is not a Gen Z problem. It is a leadership problem. If you want adoption, you cannot skip the hard work. That means training, transparency, and real conversations about how AI will be used and why. AI is not an easy button. And your people are not the barrier. They are the signal. 👇 Let’s discuss: *  Do you think Gen Z is resisting AI or responding to how it’s being rolled out?  *  How is AI impacting workload and expectations in your organization?  *  What would make AI adoption feel more intentional and less forced?  🔔 Subscribe for weekly insights on digital transformation, leadership, and emerging technologies.

What OpenAI Says vs What They’re Doing

OpenAI just released its policy vision for the “intelligence age” and at first glance, it sounds promising. But when you look closer, the story starts to fall apart. In this episode of Leading Change in the Wild, I break down OpenAI’s latest policy document and the growing gap between what AI companies say and what they actually do. Because this is not just about policy. It is about trust, accountability, and whether we should believe the narrative being presented to us. From energy subsidies to workforce impact, this document raises more questions than it answers. Here’s what I unpack: * Why OpenAI’s “pay their own way” stance contradicts real-world actions  * The role of public funding and who is actually subsidizing AI infrastructure  * The disconnect between “people-first” messaging and enterprise partnerships  * Why consulting-driven AI adoption often excludes the very people doing the work  * The limitations of how AI companies define “human-centered” roles  * The lack of real mechanisms for public and worker input  * Why this document feels more like a PR move than a true shift in strategy  The takeaway is simple. Saying “people first” is not the same as acting like it. If AI companies want trust, they need to earn it through action, not just policy statements. This is not just a technology conversation. It is a leadership one. Because the future of AI will not be shaped by what companies promise. It will be shaped by what they actually do. 👇 Let’s discuss: *  Do you trust AI companies to put people first?  *  Where do you see the biggest gap between messaging and reality?  *  What responsibility should companies have before regulation steps in?    🔔 Subscribe for weekly insights on digital transformation, leadership, and emerging technologies.