Bots & Bosses (english)

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 down even in the showcase country Singapore - What German companies in Asia have learned about trust and leadership - The cultural difference: data protection (DE) vs. hallucinations (SG) - Three concrete steps you can implement in 15 minutes **Sources:** - Dominic’s on-site conversations with companies in Singapore - [Singapore SkillsFuture Credit](https://www.skillsfuture.gov.sg/): government AI funding of up to 2,000 SGD per citizen More info at: . And here is our newsletter:

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 change everything - How our AI Marketing Lead Jürgen coordinates his team - Why too many direct reports kill quality, even with AI - Our study with FernUniversität Hagen in Marketing Review St. Gallen - Four clear steps to build your own AI team **Resources mentioned:** - [Langdock Sub-Agents](https://docs.langdock.com/de/product/agents/subagents) - [Okara](https://okara.ai/login?redirectUrl=%2Fagent%2Fcmo) (AI marketing team) - [GPT-5.4](https://openai.com/de-DE/index/introducing-gpt-5-4-mini-and-nano/) **Sources:** - [Leaders of AI / FernUniversität Hagen: Study on multi-assistant systems, published in Marketing Review St. Gallen, issue 1/2026](https://imc.unisg.ch/shop/marketing-review-st-gallen-1-2026-ai-in-marketing-strategic-operational-potential/) More info at: And here is our newsletter:

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) - [Leaders of AI - Newsletter](https://www.leadersofai.com/newsletter?utm_source=podcast&utm_medium=organic&utm_campaign=content) - [MBAI (Master Business with AI)](https://www.leadersofai.com/mbai-solo?utm_source=podcast&utm_medium=organic&utm_campaign=product) **Sources:** - [Business Insider: Meta lays off hundreds of employees because of AI – these areas are affected (2026)](https://www.businessinsider.de/wirtschaft/meta-entlaesst-hunderte-mitarbeiter-wegen-ki-diese-bereiche-sind-betroffen/) - [Handelsblatt: Human replaces robot – Why Klarna is rethinking customer service (2025)](https://www.handelsblatt.com/finanzen/banken-versicherungen/banken/kuenstliche-intelligenz-mensch-ersetzt-roboter-warum-klarna-beim-kundenservice-umdenkt/100128240.html) - [Business Insider: Already 11,000 jobs cut: Accenture lays off employees who have no AI potential (2025)](https://www.businessinsider.de/wirtschaft/accenture-entlaesst-11-000-mitarbeiter-die-kein-ki-potenzial-haben/#:~:text=Accenture%20schult%20Mitarbeiter%20auf%20die%20Nutzung%20generativer,man%20die%20Personen%2C%20erklärte%20CEO%20Julie%20Sweet.) - [Federal Statistical Office (Destatis): 13.4 million people in the labor force will reach the statutory retirement age in the next 15 years (2025)](https://www.destatis.de/DE/Presse/Pressemitteilungen/2025/08/PD25_N048_13.html) - [German Economic Institute (IW Cologne): Almost 20 million employed people will reach retirement age by 2036](https://www.iwkoeln.de/presse/pressemitteilungen/holger-schaefer-philipp-deschermeier-fast-20-millionen-erwerbstaetige-gehen-bis-2036-in-rente.html)

**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.leadersofai.com/newsletter). **Sources:** - Anthropic: _[AI Fluency Index](https://www.anthropic.com/research/AI-fluency-index)_

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 responsibilities — not “even more agents” - Our course correction as an upgrade: from “max. 7 people” to dedicated roles (Finance, Ops, Org Development), so AI can really have an impact More info at: https://leadersofai.com. And here’s our newsletter: https://www.leadersofai.com/newsletter

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 key context you need for real-world practice - The leadership playbook against hype & paralysis: check the evidence, think in scenarios, run your own tests with metrics - How you bring calm inside the company: clear guardrails, responsibilities, learning loops instead of forming camps More info at: And here is our newsletter: Sources: - [Citrini Research: 2028 GIC Report](https://www.citriniresearch.com/p/2028gic) - [Matt Shumer on X (formerly Twitter)](https://x.com/mattshumer_/status/2021256989876109403) - [Nature Scientific Reports: Negativity drives online news consumption (2023)](https://www.nature.com/articles/s41562-023-01538-4) - [Nature Scientific Reports: Negative online news articles are shared more to social media (2024)](https://www.nature.com/articles/s41598-024-71263-z) - [YouTube: AI and the economy](https://youtu.be/qAsOfJYwR40?si=n93smrK1GCThEjxs) - [Vanguard study (early 2025): AI-exposed jobs](https://corporate.vanguard.com/content/dam/corp/research/pdf/isg_vemo_2026.pdf)

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 impatience costs you ROI - Which metrics really matter (rework rate, overtime, employee turnover instead of licenses) - Five concrete steps to get out of the J-curve valley More about Leaders of AI: [www.leadersofai.com](www.leadersofai.com) Newsletter: [www.leadersofai.com/newsletter](http://www.leadersofai.com/newsletter) Sources: - [FAZ Pro Digitalwirtschaft, Feb 2025: „Der KI‑Produktivitätsschub ist da – schneller als erwartet"](https://www.faz.net/pro/digitalwirtschaft/kuenstliche-intelligenz/erik-brynjolfsson-der-ki-produktivitaetsschub-ist-da-accg-200547512.html) - [Workday, Inc. / Hanover Research, Nov 2025: „Jenseits von Produktivität: Was KI wirklich wert ist"](https://de-de.newsroom.workday.com/2026-01-15-Neue-Workday-Studie-Unternehmen-lassen-KI-Gewinne-liegen)

“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 allowed to be replaceable - How Leaders of AI rebuilt its own stack in summer 2025 - Three concrete steps you can implement this week **Sources:** - Bitkom: Definition of Digital Sovereignty. **Further links:** - AI Integration Expert (120 hours, university certificate, Fresenius University of Applied Sciences): - Leaders of AI Newsletter: - More about Leaders of AI:

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 with “less work” — without clear stop points, work simply grows back - Three AI practice rules for real relief: Intentional Pause, Sequencing, Human Grounding - A guardrail for leaders: AI doesn’t save work, AI saves friction — and for that you need new rules, ownership, and stop signals More info at: . And here’s our newsletter: **Sources** - [Harvard Business Review (2026): _AI Doesn’t Reduce Work—It Intensifies It_](https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it) - [Upwork Investors: “Upwork Study Finds Employee Workloads Rising…”](https://investors.upwork.com/news-releases/news-release-details/upwork-study-finds-employee-workloads-rising-despite-increased-c) - [Microsoft WorkLab: “Breaking down the infinite workday”](https://www.microsoft.com/en-us/worklab/work-trend-index/breaking-down-infinite-workday)

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 product development. **Key takeaways:** - Head of AI and AI developer are the fastest-growing jobs in Germany (LinkedIn 2026) - Average work experience for Head of AI: only 4.8 years - AI-exposed jobs grow twice as fast as others (Vanguard) - The real challenge is not technology, but leadership **Your three steps to become Head of AI:** 1. Build AI skills 2. Use your industry expertise 3. Become visible **Your first step:** Try Helga, our free AI recruiter. In 2 minutes, she creates a complete personnel file for your first AI assistant. → [Try Helga for free](https://www.leadersofai.com/helga-signup) **Sources:** - [LinkedIn: Jobs on the Rise 2026 – Germany’s 25 fastest-growing jobs](https://www.linkedin.com/pulse/jobs-im-trend-2026-deutschlands-25-wachstärkste-berufe) - [Vanguard: Economic and Market Outlook 2026 (PDF)](https://corporate.vanguard.com/content/dam/corp/research/pdf/Vanguard-economic-and-market-outlook-2026.pdf) - [Walczok & Bipp (2026): Do Large Language Models Evoke Affective Automation-Related Job Insecurity? Springer](https://link.springer.com/article/10.1007/s10869-026-09876-5) - [Harvard Kennedy School: Measuring Human Leadership Skills with AI Agents](https://www.hbs.edu/faculty/Pages/item.aspx?num=67197) **More from Leaders of AI:** - Newsletter: [leadersofai.com/newsletter](https://www.leadersofai.com/newsletter) - Website: [leadersofai.com](https://www.leadersofai.com/) - Our programs at a glance: [leadersofai.com/programme](https://www.leadersofai.com/programme)

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 same doesn't work 4. **Experts in silos** – Task forces without critical mass 5. **IT bottleneck** – Gatekeepers instead of enablers More information at: [leadersofai.com](https://leadersofai.com) Subscribe to our newsletter: [leadersofai.com/newsletter](https://www.leadersofai.com/newsletter) **Sources:** Deloitte (2024): State of Generative AI in the Enterprise, Q4 2024. [Link](https://www.deloitte.com/content/dam/assets-zone3/us/en/docs/services/consulting/2024/us-state-of-gen-ai-q4.pdf)

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 really used - Why trust is the real bottleneck in AI adoption - The three pillars for successful AI leadership: mindset, skills, community - Three concrete steps you can implement this week You can find more about Leaders of AI at [leadersofai.com ](http://www.leadersofai.com) For weekly updates straight to your inbox, sign up for our newsletter: [www.leadersofai.com/newsletter](http://www.leadersofai.com/newsletter) Sources: Microsoft: [Microsoft Copilot Usage Report 2025](https://news.microsoft.com/source/emea/2025/12/puenktlich-zum-jahresende-der-copilot-usage-report-2025) Deloitte: [Human Capital Trends Report 2025](https://www.deloitte.com/nl/en/services/consulting/research/human-capital-trends-report-2025.html) Harvard: [The Cybernetic Teammate](https://www.hbs.edu/faculty/Pages/item.aspx?num=67197) Insights from Global Surveys on [Trust in AI](https://learn.g2.com/trust-in-ai)

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 [leadersofai.com](https://www.leadersofai.com/) and in our [newsletter](https://www.leadersofai.com/newsletter).

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 agentsSovereignty 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 already using AI. Are you leading – or just watching?AI becomes invisible – From chatbot to infrastructure working in the backgroundThe job market transforms positively – More jobs, higher salaries, but reskilling is the bottleneckHumanity becomes a superpower – Empathy as competitive advantageNew host alert: Starting this episode, Tobi – our new AI podcast host – takes over.🔗 More about Leaders of AI: leadersofai.com 📩 Newsletter: Click here

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 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!Learn more about our work at: https://leadersofai.com

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 bubble of the 1990s. - Potentials and risks of generative AI in various industries – from medicine to education to transportation. - Why it is important to continue pursuing the enormous potential of AI despite possible setbacks and skepticism. - Examples of how balancing risks and opportunities favors fundamental technological advancements. More information can be found at: https://leadersofai.com

In this episode of "AI in 5,4,3,2,1", we explore the revolutionary influences of Large Language Models on industrial production. Dominic, founder of 'Leaders of AI', highlights how AI optimizes processes in factories and the challenges and opportunities that come with it. - Discover how LLMs analyze production data in real-time and provide recommendations for optimizing processes. - Learn how companies like Siemens and Bosch are already benefiting from internal LLMs and the advantages generative models offer. - Join the discussion on the necessity of new educational approaches and the role of AI in shaping work culture. - What strategies should companies apply to successfully integrate and scale LLMs? More information is available at: /