Bots & Bosses (english)

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)

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: /

In this episode of "AI in 5,4,3,2,1," Dominic talks about Germany's High-Tech Agenda and the key ambitions in the field of Artificial Intelligence. He examines how the crucial human factor is considered in these technological plans. - Germany's High-Tech Agenda and the goal to generate ten percent of GDP through AI by 2030. - The blind spot in the strategy: insufficient educational approaches to promote AI competencies in society. - Comparison of international educational approaches regarding AI competencies, such as in Canada and Singapore. - The importance of education and training in the AI economy for Germany and the role of 'Leaders of AI' in this context. More info can be found at: - -

In this episode of "AI in 5,4,3,2,1" we talk about data protection and compliance in AI: real risks, what the GDPR and the EU AI Act require, and how you can introduce AI pragmatically and audit-ready today. There's also a clear Leaders‑of‑AI assessment with concrete next steps. - Risks: Data leaks through AI‑agents, model inversion, third-country transfers, vulnerabilities of AI‑browsers (including Atlas-exploit). - Regulation in a nutshell: GDPR principles and DPIA; EU AI Act with risk management, documentation, logging/monitoring. - Implementation: EU hosting/on-device, clear governance, audit-ready logs; start with inventory, harden data paths, DPIA, sandbox pilot. For more information, visit: /

In this episode of "AI in 5,4,3,2,1," we talk about AI browsers like OpenAI Atlas, Perplexity Comet, and Arc/Dia: What they promise, what they actually deliver in practice, and why we currently advise companies to keep their distance. You'll get a clear Leaders-of-AI assessment with pragmatic next steps. - Promises vs. Reality: fewer clicks, faster results – but often shaky workflows and little reliable added value in tests. - Key Concerns: data protection/data sovereignty, lack of transparency, ROI that's hard to prove. - Recommendation: If testing, then small and controlled; at the same time, expand stable AI assistant workflows. More info can be found at: / / /

In this episode of "AI in 5,4,3,2,1," we talk about AI browsers like OpenAI Atlas, Perplexity Comet, and Arc/Dia: What they promise, what they actually deliver in practice, and why we currently advise companies to keep their distance. You'll get a clear Leaders-of-AI assessment with pragmatic next steps. - Promises vs. Reality: fewer clicks, faster results – but often shaky workflows and little reliable added value in tests. - Key Concerns: data protection/data sovereignty, lack of transparency, ROI that's hard to prove. - Recommendation: If testing, then small and controlled; at the same time, expand stable AI assistant workflows. More info can be found at: / / /

In this episode of the podcast "AI in 5,4,3,2,1" with host Dominic, the founder of 'Leaders of AI', the focus is on the revolutionary role of language interfaces in hybrid teams. Discover how generative AI, through large language models like ChatGPT, is changing team dynamics and increasing efficiency. - Learn how LLMs act as bridges between team members and specialized AI systems, optimizing communication. - Explore practical use cases in the fields of health research, crisis management, and finance, where language interfaces offer significant advantages. - Get to know the challenges associated with implementing such technologies and how they can be overcome through clear data quality and role structures. - Understand the importance of language interfaces as connecting nodes that reduce complexity in teams and drive innovation. More information is available at: https://link.springer.com/article/10.1007/s10791-025-09667-2?utm\_source=openai

In this episode of "AI in 5,4,3,2,1," we dive into multi-agent teams in a practical way, showing how humans, LLM-based consultants, and specialized AI workers collaborate—and why this fundamentally changes team structures. Discover how teams dynamically form, dissolve, and reform around topics, what roles the actors take on, and how clear communication guides coordination. - Understand the roles: Humans as supervisors, LLMs as consultants, specialized AI as workers—with clear handoffs. - See concrete examples: Crisis management with real-time reconfiguration, health research with faster insights, operational control with stable execution. - Recognize the benefits: more flexibility, higher agility, and quicker problem-solving—with transparent decision logic. - Know the challenges: team acceptance, clean interfaces, clear task distribution, and good parameter tuning. More information is available at: https://link.springer.com/article/10.1007/s10791-025-09667-2?utm\_source=openai

In this episode, we take a look at the Hacktivate AI Initiative by OpenAI and Allied for Startups, which has the potential to elevate Europe to a new level in the field of artificial intelligence. We demonstrate how this initiative can help Europe become a leader in AI. - The Hacktivate AI Initiative aims to accelerate the use of AI in Europe and integrate it more broadly. - In Brussels, 65 participants worked in workshops on 20 groundbreaking approaches to strengthen Europe's AI vision. - Focus on harmonizing and simplifying digital markets to promote AI usage. - The OpenAI Academy supports over two million people worldwide with AI learning resources. For more information, visit: https://openai.com/global-affairs/accelerating-ai-uptake-in-europe/?utm\_source=openai

In this episode of "AI in 5,4,3,2,1" with Dominic, the founder of 'Leaders of AI', we explore the challenges European SMEs face in adopting AI. Learn how these hurdles can become opportunities for business growth. - Comparing AI adoption today with the Internet revolution of the 90s - Utilizing AI-as-a-Service for cost-efficient implementations - Solutions for the skills shortage through partnerships and programs - Strategies for GDPR-compliant implementation of AI solutions - The cultural shift in companies for successful AI integration For more info, visit: https://xpertsoft.com/how-can-european-smes-overcome-the-challenges-of-ai-adoption/?utm\_source=openai

In this episode, we discuss why diversity and inclusion in AI teams are not only moral but also strategic design principles. We explore how diverse perspectives can improve the quality of AI products and increase their acceptance. - The importance of diversity to avoid blind spots in AI design - Structural challenges and low female participation in AI research - The use of AI to promote diversity and fairness in recruitment - The crucial role of human-machine interaction and explainability in diverse teams More information can be found at: / /

In this episode of "AI in 5,4,3,2,1," we explore the changing world of flexible human-machine collaboration. Find out why AI agents could become indispensable copilots in your work environment. - Hybrid collaborations end rigid automations, with AI agents handling routine tasks and escalating edge cases. - An example from Magdeburg shows the future of hybrid work models in the AI Co-Working Lab. - Capgemini estimates the potential of agent-based systems to be 450 billion US dollars by 2028. - Trust and human-in-the-loop are essential for the successful scaling and acceptance of these technologies. More information can be found at: / /

In this episode of the podcast "AI in 5,4,3,2,1," Dominic, founder of Leaders of AI, discusses the exciting symbiosis between humans and AI. He demonstrates how collaboration can lead to increased productivity and how companies can optimally deploy these innovative teams. - Discover the concept of the 'Centaur,' a hybrid model that combines human and artificial intelligence. - Learn how human-AI teams can be effectively organized to achieve the best results. - Practical examples: From data analysis to creative processes and design ideas—AI as a member of the team. - The future of teams: Why it is important to integrate AI as an active participant in the work process. More information can be found at: https://www.mdpi.com/2413-4155/6/4/71

In this episode of "AI in 5,4,3,2,1," Dominic, founder of 'Leaders of AI,' shines a light on an intriguing controversy in the world of Artificial Intelligence: Are large language models the right path or merely imitators of human knowledge? This discussion leads us into new horizons for learning in AI. - Richard Sutton, a pioneer of reinforcement learning, questions the scaling of large language models. - Comparison with a chef: Theory vs. practical experience in reality. - Introduction of a new approach called "Oak," an autonomous, self-learning agent. - Paradigm shift: From rigid models to dynamic, continuously learning systems. More info can be found at: https://www.youtube.com/live/XqYTQfQeMrE?t=22620s

In this episode of "AI in 5,4,3,2,1," we explore the fascinating world of AI agents and their ability to complete tasks autonomously. We highlight the latest developments and challenges that emerge in everyday life. - Functionality and potential of AI agents. - Challenges and limitations of today's AI agents. - The role of reinforcement learning environments in training autonomous systems. - How startups and large companies are investing in this technology and its significance for the future of AI. For more information, visit: https://leadersofai.com

In this episode of "AI in 5,4,3,2,1" we explore the gap between AI experiments and real business success. We explain how companies can harness the potential of AI by closing the implementation gap, known as the "Execution Gap." - The "deploy, reshape, invent" framework by Matthew Kropp - The importance of redesigning processes for real value - The path to the "invent" phase and how companies can achieve true innovation through AI More information can be found at https://leadersofai.com

In this episode of "AI in 5,4,3,2,1" we explore the future of factories and the possibility that human labor might soon no longer be needed. Learn how automation is transforming the manufacturing industry and what it means for our working world. - Learn more about Xiaomi's fully automated smartphone factory in Changping, China. - How robots, supported by AI, are revolutionizing production and ensuring consistent quality. - Impacts of automation on jobs and the necessity for new skills. - Insight into the global debate on the regulation and control of AI. More information is available at: https://leadersofai.com

In this episode of "AI in 5,4,3,2,1," we discuss a significant shift in the tech industry: Salesforce has replaced 4,000 support jobs with the use of AI. What does this mean for the business world, and how might it transform industries? - Salesforce has revitalized unused sales leads and transformed business processes with AI agents. - The seamless integration of AI systems into customer communication demonstrates the potential of human-machine interactions. - Mark Benioff views this transformation as one of the most exciting steps in his career, despite the reduction in workforce. - The business world must adapt: Automation requires new skills and new investments. More information is available at https://leadersofai.com

In this episode of "AI in 5,4,3,2,1," Dominic sheds light on the current state of the German AI landscape and its challenges. Despite billions in investments, true breakthroughs remain elusive. Now, you'll find out why. - Germany is known for engineering prowess, yet is mired in AI bureaucracy. - Complex funding processes stifle innovation. - A shortage of skilled workers hinders long-term success. - Discrepancy between research and marketable AI products. More information can be found at: &

In this episode of "AI in 5,4,3,2,1," we explore the transformative potential of AI in healthcare. From assisting doctors with routine tasks to optimizing patient care, the possibilities are astonishing. - An AI from OpenEvidence impresses with perfect results in the US Medical Licensing Examination and provides valuable support for doctors. - Bill Gates promotes innovative use of AI in Alzheimer's research with a multi-million dollar competition. - Practical applications, such as those implemented by companies like Epic Systems, are already revolutionizing the medical environment. - The true strength of AI lies in its practical and sustainable application, which must focus on the benefit to patients. More information can be found at: https://leadersofai.com

In this episode of "AI in 5,4,3,2,1", Dominic, the founder of 'Leaders of AI', sheds light on the environmental impacts of AI through a groundbreaking Google study. Discover what the reality behind the assumed burdens of AI queries looks like and what new perspective this casts on the sustainability discussion in the technology sector. - Learn how Google's "full-stack approach" enables a comprehensive overview of resource consumption. - Critics question the limits of the study and discuss overlooked factors such as indirect water consumption. - Consider the efficiency advances of Google and the paradoxical phenomenon that improved efficiency can also lead to increased use and associated burden. - Discuss the necessity for uniform standards for accurately capturing and presenting the environmental impacts of AI. More information can be found at: https://cloud.google.com/blog/products/infrastructure/measuring-the-environmental-impact-of-ai-inference?hl=en

In this episode of "AI in 5,4,3,2,1," we delve into OpenAI's exciting plans to optimize ChatGPT. It's about how AI can assist you without keeping you glued to the screen. - Explore how ChatGPT can act as a role-playing and conversation partner to support you in challenging situations. - Learn why OpenAI focuses on effective utility retention rather than screen time. - Discover how OpenAI has adjusted ChatGPT's "too nice" nature to be more useful in the long run. - Understand how ChatGPT can act as a sparring partner to organize your thoughts and boost your efficiency without constant usage. - Learn more about the integration of ChatGPT agents for tasks like scheduling appointments and managing emails. For more information, visit: https://leadersofai.com

In this episode of "AI in 5,4,3,2,1," I highlight Duolingo's "AI-first" strategy and the associated challenges. We discuss how the company dealt with resistance and what lessons can be learned for the implementation of AI. - The reaction to Duolingo's AI strategy and concerns regarding job security. - The importance of clear communication in technological transformations. - The potential of AI to support human capabilities, illustrated by Duolingo's success story. - The need to take fears and uncertainties seriously to effectively integrate technological changes. For more information, visit: https://fortune.com/2025/06/09/duolingo-ceo-surprised-backlash-ai-first-company-announcement/

In this episode of "AI in 5,4,3,2,1," we highlight the risks companies face by cutting back on AI training. We discuss why it's crucial to further develop employee skills to ensure long-term competitiveness. - 33% of employees in Germany lack important skills for their current role. - Only 30% of companies use competency data in strategic workforce planning. - Talent acquisition: Only 56% of job offers are accepted. - Employee satisfaction vs. silent frustration and its impacts. More information can be found at https://leadersofai.com and https://www.mckinsey.de/news/presse/2025-07-21-hr-monitor-2025

In this episode of "AI in 5,4,3,2,1", we focus on OpenAI's job predictions from 2023, which have proven to be remarkably accurate. According to an analysis by Microsoft, these predictions could significantly change your perspective on the job market. - OpenAI's forecasts on AI-affected jobs and the surprisingly high accuracy as stated by Microsoft. - Which professions are most affected, such as translators, customer service employees, and writers. - The challenges and opportunities that arise from the integration of AI into everyday work life. More information can be found at https://leadersofai.com

In this episode of "AI in 5,4,3,2,1," we talk about a revolutionary AI project from Switzerland that emphasizes transparency and accessibility. An open language model, which will be available worldwide for free, is changing the game for innovation in companies. - The Swiss AI model, which understands over 1,000 languages and is openly accessible - Discussion on the benefits of open research approaches and transparency in AI - Insights into the technical infrastructure and sustainable practices behind the project More information can be found at https://leadersofai.com

In this episode, we talk about the introduction of the autonomous software engineer Devin at Goldman Sachs. This episode highlights the role and potential of AI in corporate structures, especially at one of the largest financial institutions on Wall Street. - Devin is an autonomous software engineer from Cognition and joins the development team at Goldman Sachs. - Use of AI to increase productivity and relieve human developers from routine tasks. - Challenges and opportunities of a hybrid workforce of humans and machines. - The significance of implementing AI as a model for other companies. For more information, visit https://leadersofai.com and https://www.cnbc.com/2025/07/11/goldman-sachs-autonomous-coder-pilot-marks-major-ai-milestone.html