Seth Earley is a Chemist by training and an expert on AI. Specifically, how AI is used to improve knowledge management. In fact, he wrote the book on the topic titled “The AI-Powered Enterprise” in which he explains the importance of ontologies when applying AI. Seth is the CEO of Earley Information Science. He has been advising companies on technology strategy since 1994 and is currently focused on AI and knowledge engineering. 

Listen and learn: 

1. Seth’s contribution to AI history… including the term he coined that was co-opted by former IBM CEO Ginni Rometty 
2. Why all AI is a data (and information architecture) problem 
3. How the Applied Materials field services team reduced time spent finding information by 50% with knowledge engineering and ontologies 
4. Why proper information architecture is required for virtual agents to reduce call volume and help live agents 
5. What has changed since Seth first published his AI book in 2020 
6. The benefits of semantic search vs. traditional keyword search 
7. Where to start with a knowledge management strategy 
8. Why “data scientists spend more time being data janitors” 
9. How to mitigate the impact of bias in AI training data 

References in this episode: 

• How AI can detect employee burnout
• The Innovation Delusion on Amazon 
• Earley Information Science
• The AI-Powered Enterprise on Amazon 
• Kevin Dewalt, Prolego CEO, on AI and the Future of Work