Episode Summary This episode explores a topic most business leaders are not thinking about yet, but probably should be. AI systems are built on content, and a huge portion of that content comes from books. In this conversation, we dig into what that means for authors, publishers, and everyday users of AI tools like ChatGPT, Claude, and Gemini. Julie explains how large language models became dramatically more capable once they began ingesting high-quality book content, often without permission. She walks through the legal and ethical tensions this created, including why the rules in Europe are very different from those in the United States. We also unpack what AI can and cannot reliably tell you about a book, why you may not be getting the actual methodology you think you are, and how the industry is moving from the “scraping era” into a new phase of licensed and traceable content. Beyond rights and regulation, the episode covers how authors can responsibly use AI as a writing and marketing partner, why originality matters more than ever, and how smaller, more focused books may be the future. If you care about content, creativity, trust in AI outputs, or where business knowledge actually comes from, this is a conversation that will reshape how you think about AI-powered tools. Guest Introduction Julie Trelstad is a 30-year publishing industry veteran and the Head of U.S. Publishing at AMLIT.ai. She has worked across nearly every corner of modern publishing, from major publishing houses to global digital distribution, and now sits at the center of one of the most urgent conversations in AI: how authors’ work is used, protected, and compensated in the age of large language models. Julie is a leading voice on digital rights, AI training data, and the future of content ownership for authors and publishers. AI Challenge Call-to-Action This week’s AI Challenge is inspired directly by the conversation with Julie. Challenge: Learn how to trust but verify AI outputs. You will practice: Testing AI answers against original source material Understanding where AI summaries may break down Building a habit of validating AI-generated insights before using them in your work Get the full step-by-step instructions here: 👉 https://www.promptthis.ai/blog/why-ai-hallucinations-happen-and-how-to-prevent-them If you have an AI story or business use case to share and want to be on the show, head to the Contact Us page at promptthis.ai and let us know. Chapter Breakdown 00:00 – Introduction Why this episode matters and how AI intersects with publishing and content ownership. 02:00 – Julie’s Path Into Publishing and Digital Rights From early desktop publishing to ebooks, audiobooks, and now AI-era rights advocacy. 04:30 – How AI Models “Ate” Books Why large language models improved so quickly and why authors are pushing back. 06:45 – Lawsuits, Settlements, and the Scraping Era What recent legal cases reveal about how AI companies sourced content. 08:15 – Digital Fingerprints and the ISCC How content identification works and why it matters for protecting authors. 09:55 – U.S. vs. Europe: Two Very Different Rulebooks Why European authors have stronger protections and what that means globally. 11:30 – Can You Trust AI Answers About Books? Why AI summaries may not reflect the original work or its intent. 13:20 – Using AI With Books You Own What is allowed, what is risky, and how personal use fits into the picture. 15:10 – The Future of AI and Specialized Models Why smaller, trusted models may outperform general-purpose LLMs. 17:00 – Accessibility, Learning Differences, and Publishing Gaps How AI could improve access for readers, and where publishing has fallen behind. 20:50 – Predictions for Authors and the Industry Where rights, discovery, and compensation may be headed next. 22:30 – Writing in the Age of AI Slop How authors can use AI without losing originality or voice. 24:30 – Practical AI Tools for Writers and Creators A rundown of tools that help with research, editing, and organization. 27:30 – Should Business Leaders Write Shorter Books? Why focused, problem-driven books may outperform traditional long formats. 31:15 – When Authors Should Engage with AMLIT What happens after publication and how rights protection begins. 34:00 – This Week’s AI Challenge How to build trust into your AI workflows. 35:30 – Where to Learn More How to connect with Julie and continue the conversation.
