Energy and the AI Race: Why Power Is the Real Bottleneck for Artificial IntelligenceShape
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AI isn’t limited by models, talent, or capital — it’s limited by electricity.
In this episode of the Macro AI Podcast, Gary Sloper and Scott Bryan break down the energy reality behind artificial intelligence, from individual AI usage to hyperscalers and national infrastructure strategy. They explain where AI actually consumes power, why your laptop is just the remote control, and how every prompt to a large language model triggers real energy use inside GPU-powered data centers.
The conversation scales from home offices to enterprises, introducing the concept of the “shadow data center” — the hidden energy footprint organizations incur when using AI through SaaS platforms and APIs. Even without owning infrastructure, businesses are consuming significant AI-driven electricity at scale.
Gary and Scott then examine how many gigawatts of new data center capacity are being planned in the U.S. and globally, why grid timelines are becoming the true bottleneck for AI growth, and how energy availability is reshaping competition between the United States and China.
Bottom line: AI strategy without energy awareness is incomplete. The future of AI will be written in code — but powered by electrons.
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About your AI Guides
Gary Sloper
https://www.linkedin.com/in/gsloper/
Scott Bryan
https://www.linkedin.com/in/scottjbryan/
Macro AI Website:
https://www.macroaipodcast.com/
Macro AI LinkedIn Page:
https://www.linkedin.com/company/macro-ai-podcast/
Gary's Free AI Readiness Assessment:
https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness
Scott's Content & Blog
https://www.macronomics.ai/blog
