Meisa Bonelli

Thinking Through AI

Business EN ↓ 4 episodes

Thinking Through AI is a working analysis of how artificial intelligence is actually being understood, deployed, and operationalized. Hosted by Meisa Bonelli, this series examines AI through the lens of executive operations, applied implementation, and systems thinking, focusing on how organizations move from concept to execution. Each episode explores the gap between what is promised and what is delivered, with attention to decision-making, governance, and real-world constraints. Rather than chasing trends, the focus is on clarity: how leaders interpret AI, how teams implement it, and where f...

Author

Meisa Bonelli

Episodes

Ep. 4 - Algorithmically Blackballed: What Happens When Every Employer Uses the Same AI 02.07.2026 54:34

Artificial intelligence is rapidly becoming embedded in hiring, but the most important question may no longer be whether a single algorithm is biased. The larger issue is what happens when large portions of the labor market rely on the same underlying systems to make decisions about who gets seen, who advances, and who gets left behind. Drawing on Stanford's research into algorithmic monocult...

Ep. 3 - China Understands The Assignment 02.06.2026 10:15

For the past year, much of the AI conversation has focused on chips, models, and capital. But what if those aren’t the only metrics that matter? In this episode, I explore whether we're measuring AI competition correctly. While America continues to lead in frontier model development, China appears to be focusing heavily on adoption, workforce readiness, industrial deployment, and practical AI...

Ep. 2 - The White-Collar AI Narrative Is Getting Lazy (Augmentation Isn’t Replacement) 22.05.2026 10:07

This episode was sponsored by the, " AI Adoption Leadership Audio Briefing ." AI is absolutely changing white-collar work, but the conversation around what gets disrupted, compressed, or replaced has become dangerously oversimplified. Not all knowledge work is structurally the same. What works in software engineering doesn’t automatically map cleanly onto law, compliance, healthcare, fi...

Ep. 1 - China is Practicing. We're Still Planning. 16.04.2026 6:16

What if the future of AI leadership isn’t about who builds the best models, but who learns how to use them fastest? This piece explores a critical gap in the AI conversation: the difference between access and understanding. As global competition intensifies, the real advantage may come from societies that treat learning as a shared, cross-generational system, not an individual responsibility. This...