Show Notes
Generative AI trust is becoming one of the biggest leadership challenges in business. In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Alice Sesay Pope, author of The Trust Algorithm: How Leaders Build Trust with Generative AI, about why AI success cannot be measured only by speed, automation, or cost reduction.
Alice describes a growing “trust recession” where customers are unsure whether brands are acting in their best interest, employees are unsure whether AI will help or replace them, and leaders are under pressure to prove AI ROI before they have built the right strategy, governance, and human oversight. The conversation explores why AI customer service often disappoints, why bad data can mislead both chatbots and human agents, and why companies should not deploy generative AI just to say they are using it.
You will also hear why leaders need to think about token costs, risk, guardrails, change management, psychological safety, reskilling, and privacy before scaling AI across the business.
This episode is for founders, executives, consultants, marketers, customer experience leaders, and anyone trying to understand how to use generative AI responsibly without losing customer trust.
Key Takeaways Why we are entering a generative AI trust recession Why AI customer service can damage brand loyalty Why AI ROI fails when leaders focus only on cost cutting Why human oversight and verification still matter Why reskilling employees is a leadership responsibility Why agentic AI creates new trust and privacy questions Why companies need AI governance before scaling AI
Get My Newsletter 📧💌📧 Tune in to get my thoughts and all episodes. Don't forget to subscribe to our Newsletter: https://beginnersguide.nl 📧💌📧
About Dietmar Fischer Dietmar Fischer is a podcaster and AI marketer from Berlin. If you want help with AI strategy or digital marketing, visit: https://argoberlin.com
Quotes from the Episode “We are in a trust recession.”“Don't just use AI just to be utilizing. Use it purposefully.”“There's no technology solution that I believe can be effective without thinking of the human impact.”
Chapters 00:00 Opening and Alice’s AI background 01:38 The Trust Algorithm and the trust recession 04:13 Why AI answers still need human verification 08:34 When customer service AI gets trust wrong 13:56 Why leaders need AI strategy, ROI, and guardrails 20:20 Human impact, reskilling, and change management 30:13 AI agents, privacy boundaries, and practical executive use cases
Where to Find Alice Website: AliceSesayPope.com LinkedIn: Alice Sesay Pope Book: The Trust Algorithm: How Leaders Build Trust with Generative AI Hosted on Acast. See acast.com/privacy for more information.
More from A Beginner's Guide to AI
AI agents are becoming more capable, more personal and much harder to ignore. They can use connected apps, prepare work in the background and act on your behalf. So why are Big Tech companies making them look like cheerful little creatures with giant eyes?
🤖 Why AI Transformation Needs Intentionality, Not More Technology
🤖 AI has moved beyond technical teams and innovation labs. At Berlin’s BIG BANG KI Festival, Dietmar Fischer found packed stages, long queues, and business professionals searching for practical ways to implement artificial intelligence.
🤖 AI fluency is becoming a core business skill. But being AI fluent means much more than knowing how to prompt ChatGPT. In this episode of Beginner's Guide to AI, Dietmar Fischer talks with entrepreneur and growth marketer Solomon Thimothy about the transition from using AI as a chatbot to using AI as part of the workforce.
⚡ AI is getting cheaper, faster, and more efficient. So why are data centres preparing to use far more electricity? In this episode of A Beginner’s Guide to AI, Professor GePhardT explores Jevons’ paradox and its uncomfortable lesson for artificial intelligence: using less energy per task does not guarantee that we use less energy overall.