The numbers are extraordinary. OpenAI expects to spend $121 billion on compute โ as explored in the economics of AI compute infrastructure โ in a single year. Anthropicโs training costs start at near zero relative to revenue, then collapse as a share of sales faster than any comparable technology business in history.
These are not tech company financials. They are the economics of an arms race dressed in a spreadsheet.
But the more important story isnโt the raw numbers. Itโs the structural divergence between two companies that appear to be in the same business โ building frontier AI models โ but are executing two fundamentally different bets on how to survive, scale, and eventually dominate.
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Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur, HackerNoon and Search Engine People. Find him on LinkedIn and Substack. See how we source.
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