
In this episode of the AI Experience Book Club, Julien Redelsperger looks at AI-Powered Leadership, by Dave Silberman, Rich Maltzman, Loredana Abramo, and Vijay Kanabar, published in March 2025 by Addison-Wesley Professional.
The book explores how artificial intelligence is changing the role of leaders and managers as it becomes more involved in analysis, recommendations, and decision-making. It argues for an approach in which human capabilities and AI complement each other, with particular attention to judgment, critical thinking, data quality, and bias. In this episode, you’ll discover why an AI-generated analysis can be accurate without necessarily leading to a good decision, how to use AI to challenge your own assumptions, and why human accountability remains essential as these systems become more capable.
The episode also looks at some of the book’s limitations: what should you do when your experience conflicts with the algorithm? How should responsibility be divided between humans and machines? And what happens to productivity gains when AI becomes fully integrated into everyday work?
Hosted on Ausha. See ausha.co/privacy-policy for more information.

In this episode of the AI Experience Book Club, Julien Redelsperger looks at AI-Powered Leadership, by Dave Silberman, Rich Maltzman, Loredana Abramo, and Vijay Kanabar, published in March 2025 by Addison-Wesley Professional.
The book explores how artificial intelligence is changing the role of leaders and managers as it becomes more involved in analysis, recommendations, and decision-making. It argues for an approach in which human capabilities and AI complement each other, with particular attention to judgment, critical thinking, data quality, and bias. In this episode, you’ll discover why an AI-generated analysis can be accurate without necessarily leading to a good decision, how to use AI to challenge your own assumptions, and why human accountability remains essential as these systems become more capable.
The episode also looks at some of the book’s limitations: what should you do when your experience conflicts with the algorithm? How should responsibility be divided between humans and machines? And what happens to productivity gains when AI becomes fully integrated into everyday work?
Hosted on Ausha. See ausha.co/privacy-policy for more information.