The Prof G Pod with Scott Galloway Why CEOs Are Getting AI Wrong — with Ethan Mollick
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Feb 12, 2026 
Ethan Mollick, Wharton professor and author exploring how AI reshapes work and education. He tackles why CEOs misunderstand AI, the quiet productivity gains changing jobs, and the need to redesign organizations around new tools. He also covers AI in higher education, medicine, and the implications of open-weight models for the workforce.
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More Output Can Create Organizational Bottlenecks
- Individual gains can flood systems with more output, creating process bottlenecks for organizations.
- The real value requires redesigning workflows, not just automating existing tasks.
Start With A Paid Big-Model Subscription
- Subscribe to a major model (OpenAI, Anthropic, or Gemini) and use their advanced "thinking" model for serious work.
- Spend 8–10 hours testing AI on real job tasks to map strengths and weaknesses.
Model Size And Infrastructure Drive Dominance
- Scaling laws favor a few firms that can build ever-larger models because size improves performance broadly.
- The AI race is resource-driven: data centers, chips, and capital determine who competes at the frontier.