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by Dominic von Proeck
10 humans. 50+ AI colleagues. A company that feels like science fiction – but it's just our Tuesday. In "Bots & Bosses" we share what we learn at Leaders of AI every single day: Which AI assistants shine, which ones mess up spectacularly, and why Jürgen – our AI team lead – still got promoted. Twice. This podcast is 100% AI-generated. No microphone was used in its creation. We deliberately left in all the mistakes the AI makes – because we want to show you where the real limits are. That said, we think the result is pretty damn impressive!
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In this episode, it’s about Dominic’s digital twin and the question of why a twin is not a replacement for leadership, but a tool to make leadership logic available in hybrid organizations.You will learn:why a digital twin is more than a copywhy leadership principles in agentic organizations must be made explicitwhy orientation matters more than perfect imitationwhat happens when teams and AI systems work more independentlywhy strong AI organizations don’t fail because of models, but because of vaguenessMore info at: https://leadersofai.com.And here is our newsletter: https://www.leadersofai.com/newsletter
In this episode, it’s about the AI paradox: why strategically outsourcing routine work to AI does not automatically make us more superficial, but—at best—can help us reflect better. You’ll learn: - why the debate about “lazy-thinking students” misses the point - what Wang and Zhang found in their study with 912 students - why cognitive offloading does not automatically mean less thinking - why efficiency and critical review do not contradict each other - what we mean by the term Homo Agenticus Sources and mentions: - Wang & Zhang (2026): - More about Leaders of AI: - Newsletter:
In this episode, it’s about how self-learning AI is shaping our marketing – and why this creates a new leadership task. You’ll learn: - why our LinkedIn performance suddenly dropped, even though we had good content - how a second agent analyzes the data and directly improves the skills of the first - why marketing is an ideal starting point for self-learning AI systems - why the real challenge is not technology, but leadership - why in the future the key question won’t be whether AI learns, but where it learns toward Sources and mentions: - Business Punk column by Dominic von Proeck, published on 01/06: - More about Leaders of AI: - Newsletter:
In this episode, it’s about a surprisingly simple insight from 81,000 interviews: people mainly want AI when it saves time, helps them do better work, and speeds up learning. You’ll learn: - why this insight matters more for companies than it seems at first - which three motives are behind real AI adoption - why unreliability and job worries remain the biggest brakes - why leaders need to translate AI not through tools, but through specific use cases - why reliability is the real lever for adoption Sources: - Anthropic: What 81,000 people want from AI: - More about Leaders of AI: [https://www.leadersofai.com](https://www.leadersofai.com/) - Newsletter: - Blog: [www.leadersofai.com/blog/was-81-000-menschen-von-ki-wollen](www.leadersofai.com/blog/was-81-000-menschen-von-ki-wollen)
In this episode, it’s all about the Claude hype—and the strategically more important question behind it: What does Claude show us about the next level of maturity for AI in everyday work? You’ll learn: - why Claude feels like the first real work assistant for many people right now - which features make the difference: large context, Artifacts, Extended Thinking, and integrations - why justified hype is no reason for hectic tool switching - which three questions you should ask before any migration - why AI only scales with roles, responsibilities, and leadership - why, in content work, AI can also be a corrective against over-dramatizing Sources and mentions: - Anthropic, Claude Model Docs: - Anthropic, Token efficient compaction: - Anthropic, ServiceNow Case Study: - CNBC, Claude Cowork Update, 24/02/2026: - Financial Times, note on more moderating AI answers: More on Leaders of AI: [https://www.leadersofai.com](https://www.leadersofai.com/) Newsletter:
In this episode, it’s about the five most important AI insights from OMR 2026: 1. Agentic AI is here. AI is moving from a tool to a co-worker. 2. AI is changing search — and with it, all of marketing. 3. Europe’s digital sovereignty is becoming a strategic question. 4. AI start-ups are booming, but the market is moving toward consolidation. 5. The mindset is shifting from fear to co-pilot. Our take: OMR 2026 showed that these topics no longer belong on “future” panels. They are execution topics now. You can find more about Leaders of AI at leadersofai.com For weekly updates in your inbox, sign up for our newsletter: [www.leadersofai.com/newsletter](http://www.leadersofai.com/newsletter) **Sources:** - OnlineMarketing.de: OMR 2026 Hamburg Event Recap AI Future: - Meedia: Artificial intelligence is changing everything, including OMR 2026: - Contentmanager: OMR 2026: These trends and developments shape the festival: - Marketingscout: Between the AI revolution, world stars, and Europe’s digital sovereignty: - Kress: OMR Festival 2026: The sentences that stick: - Basic Thinking: OMR 2026 experiences: - GQ: OMR 2026 highlights: - Android Digital: OMR 2026: The future of digitalization:
In this episode, we talk about **three things** that belong together: - Why AI is not a technology project, but a stress test for the organization - Why, according to PwC, 74 percent of AI value ends up with only 20 percent of companies - Why falling inference costs make AI an infrastructure decision **Our take:** The best models don’t win. The winners are the organizations that set up roles, processes, and responsibility in a clean and clear way. **Sources:** - PwC, AI Performance Study 2026: - Artificial Intelligence News, NVIDIA and Google infrastructure cuts AI inference costs: - More about Leaders of AI: [https://www.leadersofai.com](https://www.leadersofai.com/) - Newsletter:
Many AI initiatives fail not because of models or licenses, but because key roles are missing in the organization. In this episode, we talk about why AI assistants are really organizational design, and how you can use a simple role framework to clearly set responsibilities, quality standards, and handovers. ### In this episode - Why AI becomes a meeting topic when there are no roles - Gartner forecast: Why many autonomous AI systems will be stopped by 2027 - The role framework: task, responsibility, handover, rules - Practical example Britney: Brand manager as an AI role ### Sources - Gartner Newsroom (2025): Forecast on the cancellation rate of agentic or autonomous AI projects by the end of 2027. (Please add the link in the editorial team with the exact Gartner Newsroom article.) More info at: Here is our April offer: [Spring Special](https://www.leadersofai.com/specials-multi/spring-special#offer) And here is our newsletter: [Newsletter Sign-up](https://www.leadersofai.com/newsletter)
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10 humans. 50+ AI colleagues. A company that feels like science fiction – but it's just our Tuesday. In "Bots & Bosses" we share what we learn at Leaders of AI every single day: Which AI assistants shine, which ones mess up spectacularly, and why Jürgen – our AI team lead – still got promoted. Twice. This podcast is 100% AI-generated. No microphone was used in its creation. We deliberately left in all the mistakes the AI makes – because we want to show you where the real limits are. That said, we think the result is pretty damn impressive!
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