Bots & Bosses (english)

In this episode, we look at a simple but often overlooked question: Does the human even appear in your AI strategy? We show why many strategies fail because of too much focus on tools and too little implementation logic. And why falling inference costs are making that gap even more visible right now. You’ll learn: - why AI strategy is leadership work - which three questions you can immediately app...

AI FOMO is real. Especially right now, when it feels like new always-on assistants are launching every week. In this episode, we break down: - why new AI assistants are not automatically immediately relevant for your company - what’s behind OpenAI Dots, Microsoft Copilot Autopilot, Meta Muse, OpenClaw, and Hermes Agent - why governance is the real bottleneck - which three questions you should answ...

Sources Dominic’s conversations with a private equity firm, the service company of a major AI lab, and a startup from Y Combinator (anonymized background conversations, no public links) Andreessen Horowitz: State of Markets II ChainCatcher: Summary of the report “State of Markets II” Amazon Web Services: AWS Global Startup Trends Report Softprom: AWS Engines of Growth 2026 heise online: Massive tr...

Summary: Jev is not a topic just because it is loud right now. For us, it is an early indicator. In this episode, we explain why new AI names only become relevant when they truly change something for companies: in costs, processes, dependencies, and operational execution. Key Topics: - What Jev actually is: a decision model instead of a classic language model - Why specialized models for routing,...

Agents or operating system? For three episodes, we explored this question. In the grand finale of our series, we resolve it and present a third approach: Fluid Teams. In this episode, you will learn: - Why the question “agents or operating system” is the wrong question - What connectability means and why it decides the value of AI - How the formula “value equals quality times connectability” works...

An AI system that can do everything, knows everything, and connects all departments. Sounds perfect. We tested it for six months in parallel with our 53 AI assistants. The result surprised even us. In this episode, you’ll learn: - What makes the AI operating system different from the agent approach - Why a system without a face and a role does not build trust - How an AI system checks itself, and...

AI agents are a turbo boost in companies mainly because they make trust, roles, and responsibilities visible—not because of some technical trick. In this episode, you’ll learn why agents fit into everyday work so quickly, and how clear leadership logic helps you keep adoption, quality, and governance stable. - Why AI projects rarely fail because of tools—but because of unclear goals, vague respons...

In this episode, it’s about a simple but crucial idea: Europe’s AI future will not be decided by models, but by execution, enablement, and how organizations apply AI. You’ll learn: Why the real AI bottleneck in Europe is not attention, but application Why access to tools alone does not create an advantage Why teams, processes, and enablement will matter more than the next big AI announcement More...

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 copy why leadership principles in agentic organizations must be made explicit why orientation matters more than perfect imitation what happens when teams and AI...

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 eff...

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...

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 translat...

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 hy...

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 tak...

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, proc...

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 fore...

Singapore is seen as a showcase country for AI: sixty seconds to enter the country with facial recognition, government support of up to two thousand dollars per citizen. Dominic was there and spoke with companies like Adidas, Porsche, and KSB. The key insight: Behind the shiny surface, companies struggle with the same problems as in Germany. **In this episode:** - Why AI transformation is slowing...

Langdock has launched sub-agents, GPT-5.4 now delegates internally to smaller models, and you can get whole AI marketing teams for $99 a month. In this episode, we show why this is not a tool question, but a question of organizational design, and we share our learnings from more than a year of hands-on work with multi-assistant systems. **In this episode:** - What sub-agents are and why they chang...

Why AI-driven layoffs often lead into an expensive cycle (cut jobs → quality problems → buy back at high cost), why demographics are turning the calculation upside down in Germany, and which three leadership questions you should answer now. **Links & Recommendations** - [Leaders of AI - Programme](https://www.leadersofai.com/?utm_source=podcast&utm_medium=organic&utm_campaign=product#mbai-info) -...

**In this episode:** - Why AI fluency starts with review - What the Anthropic AI Fluency Index shows about iteration and review behavior - A 3-checkpoint system for teams: sources, risk, approval - Why polished outputs are the most dangerous trust trap You can find more info about Leaders of AI and our programs at [leadersofai.com](http://leadersofai.com) and in our [newsletter](https://www.leader...

Over €1M in revenue per person — and still we were close to driving our “growth only with AI” experiment straight into a wall. This episode is about the uncomfortable truth: AI is rarely the bottleneck. Processes are. - Why extreme efficiency suddenly feels like chaos: seven research projects, no clear operating system - What was missing: templates, dashboards, clear quality criteria, clear respon...

AI is often either a “wonder weapon” or “the end of the world” in the media — and that is exactly what makes many organizations nervous. In this episode, we talk about why dystopia gets so many clicks and how, as a leader, you steer with a system instead of headlines. - Why negative AI headlines dominate: attention = emotion, and fear is the strongest driver - Three common panic claims — plus the...

The AI productivity boost is measurable: US productivity +2.7% (Stanford, Brynjolfsson). But many companies see no ROI—not because AI doesn’t work, but because they (1) are in the middle of a transformation and (2) measure the wrong things. In this episode, you’ll learn: - Why the AI productivity boost is becoming visible in the US (and not here yet) - What the productivity J-curve is and why impa...

“Get out of Big Tech” is a nice impulse, but not a strategy. In this episode, Tobi explains why digital sovereignty is an architecture decision—and how Leaders of AI puts it into practice. **In this episode:** - Why “Europe only” is just as risky as “put everything in the US cloud” - The three tension fields: data protection, competitiveness, convenience - What must stay with you—and what is allow...

AI makes output cheap — and still increases the workload if your system can’t handle the new speed. This episode is about “workload creep”: how AI quietly creates more work, and what you can do right away with three simple team rules to stop it. - Why AI often doesn’t reduce work, but instead boosts task expansion, ambient work, and multitasking - The core mistake: “create faster” gets confused wi...