Has the AI Witch Hunt Begun?

AI companies spent years telling us to adopt AI or risk getting left behind. Now, using AI could get your content labeled, flagged, or even reported. So, has the AI witch hunt begun? In this episode of Leading Change in the Wild, I break down the growing push toward AI watermarking, LinkedIn’s AI content reporting features, and the broader effort to label content that has been created or even edited with artificial intelligence. The goal is to rebuild trust. But are we actually solving the problem, or just shifting the blame to the people who were told to use these tools in the first place? Here’s what I unpack: Why Anthropic is introducing watermarking for AI-processed text LinkedIn’s approach to reporting AI-generated content Why AI-assisted content is not necessarily AI-created content Where we draw the line between tools like spellcheck, Grammarly, and generative AI How AI companies helped create the trust problem they are now trying to solve Why labeling everything that touches AI may create even more distrust The need to bring purpose and intentionality back into how we use AI The takeaway is clear. The problem is not simply whether AI touched a piece of content. The bigger question is why we are using AI in the first place. There is a massive difference between outsourcing our thinking and using technology intentionally to help us create, solve problems, and do things we could not do before. If we want to rebuild trust, labeling people for using AI may not be the answer. We need to get back to purpose. Let’s discuss: Do AI watermarks actually make you trust content more? Where should we draw the line between AI-assisted and AI-generated content? Is labeling AI content solving the trust problem, or making it worse? Subscribe for weekly insights on digital transformation, change management, leadership, and emerging technologies.