Is AI Still in 1995? Gene Munster and Doug Clinton on the Next Phase of the AI Boom

AI is moving from hype to real enterprise adoption, and Gene Munster and Doug Clinton join Excess Returns to explain what that means for investors, technology stocks, energy demand, jobs and the next phase of the AI trade. We discuss why AI may still be early in its bubble cycle, how frontier models like GPT, Claude, Gemini and Grok compare, why AI-powered investing is becoming more practical, and where the biggest second-order opportunities may emerge.Gene Munster on Xhttps://x.com/munster_geneDoug Clinton on Xhttps://x.com/dougclintonDeepwater Asset Managementhttps://www.deepwatermgmt.com/Intelligent Alphahttps://www.intelligentalpha.co/Main topics covered:• Why Doug Clinton still thinks AI could become a bigger bubble than dot-com• How Claude Code, Codex and frontier AI models are changing enterprise productivity• The job disruption risk for knowledge workers and why AI adoption may become a survival skill• Why the AI model race may not be winner-take-all• How Intelligent Alpha uses large language models to evaluate stocks and earnings expectations• Why GPT, Claude and DeepSeek perform differently across investing tasks• The AI infrastructure boom and why energy may be one of the most underappreciated bottlenecks• Hyperscaler CapEx, data centers and the investment case for continued AI spending• How major AI IPOs like SpaceX, Anthropic and OpenAI could affect public markets• Why space, orbital data centers and zero-gravity manufacturing could become real investment themesTimestamps:00:00 AI, electricity and intelligence04:33 Why new AI models changed the semiconductor trade09:14 What AI means for knowledge worker jobs14:03 Codex, Claude Code and Google’s AI challenge18:50 OpenAI, Apple and the model capacity race23:03 How many frontier AI models can survive?27:18 Intelligent Alpha’s AI earnings benchmark31:34 Why AI investors avoid emotional bias35:33 Where to invest in the AI stack39:00 Why AI energy demand is still underappreciated43:43 How markets are judging hyperscaler AI spending48:00 The investment opportunity in space52:20 Final thoughts and closing