Bots & Bosses (english)

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...

LinkedIn names Head of AI as the number one trending job in Germany. In this episode, we analyze the data, show the strategic implications for your career path, and share our observations from working with more than 2,100 leaders during AI transformation. Plus: three concrete steps to help you make the jump into an AI leadership role—no matter whether you come from marketing, operations, or produc...

Sixty-eight percent of companies fail to move their AI experiments into production. The problem? It's not the technology – it's leadership. In this episode, we discuss the five most common leadership mistakes: 1. **The ROI trap** – Measured too early, too narrowly 2. **Delegation instead of leading** – Leadership doesn't use AI themselves 3. **One-size-fits-all training** – Training everyone the s...

82% of employees have never had any AI training. At the same time, leadership teams expect 30% more productivity. Microsoft analyzed 37 million Copilot requests, and the result is surprising: people don’t use AI for efficiency, but to communicate in a more human way. In this episode, you’ll learn: - Why we changed our claim to “Tomorrow is human” - What the Microsoft study reveals about how AI is...

In this episode, we discuss why prompting is dead and can never work as a pervasive enterprise strategy. You'll also learn how to become productive with AI instead and ensure consistently high quality using prompt assistants. [Here's the free download of our prompt assistant Helga](https://www.leadersofai.com/helga-signup) (or as we call her: "AI Recruiter"). Learn more about Leaders of AI at [lea...

72% of companies use AI – but only 23% make it out of the pilot phase. To be on the winning side in 2026, here are our six predictions: Governance becomes a C-level priority – No more siloed solutions and five parallel travel expense agents Sovereignty becomes an architecture question – Where do you need data control, where is the US cloud enough? Shadow AI forces you to lead – Your people are alr...

10 humans. 50+ AI colleagues. A company that feels like science fiction – but it's just our everyday reality. 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 a week. Five minutes. Zero bullshit. This podcast is 100% AI-generated. No microphone...

In this episode, we discuss whether artificial intelligence is a bubble and why that might not matter. AI could be the most significant bubble we've ever needed. We shed light on the current skepticism surrounding the overvaluation of AI technology and how this compares to important historical innovations. - The role of exaggeration and greed in technological innovations, similar to the internet b...