"AI stands at the same crossroads today. The platforms consumers know best - ChatGPT, Gemini, Claude - are extraordinary feats of engineering, but they don't represent sustainable AI. They are breathtakingly expensive to run, but free or cheap to use. They deliver entertainment and convenience more than enterprise value. It's fun to have ChatGPT turn out a poem, nice when it helps you smooth out an email - but it's not mission-critical."
"Take Austin, Texas, where an on-premise AI-system helped local government process building permits in days instead of months. No spectacle. No headlines. Just efficiency gains that will outlast the market cycle. That's the point too often missed in the frenzy. Mega-models attract headlines, consume billions in capital, and struggle to demonstrate sustainable economics. Meanwhile, smaller, domain-specific systems are already delivering efficiency gains, cost savings and productivity improvements. The smart play isn't to abandon AI, but to pivot toward models and deployments that will endure."
Rapid stock jumps for established tech firms reflect investor exuberance tied to AI hype and have pushed indices to record highs. Hyperscale mega-models attract capital and headlines but face unsustainable economics due to enormous training and operating costs and limited enterprise ROI. Domain-specific and on-premise AI deployments are already producing concrete efficiency gains, cost savings, and productivity improvements in real-world use cases like municipal permitting. Historical parallels with Netscape show that flashy consumer platforms can fade while foundational infrastructure and practical applications create lasting value. Strategic investment should prioritize durable, economically sustainable AI models and deployments over headline-grabbing scale plays.
Read at Fortune
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