Azeem Azhar's Exponential View Inside the economics of OpenAI (exclusive research)
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Feb 13, 2026 
Matt Robinson, financial journalist and founder of AI Street, probes AI company finances. Hannah Petrovic, research lead with an astrophysics background, reconstructed OpenAI’s public unit economics. Jaime Sevilla, founder of Epoch AI, analyzes scaling laws and compute trends. They examine OpenAI’s tight operating economics, model depreciation, infrastructure bottlenecks (GPUs vs energy), rising compute demand from persistent agents, and ad-driven revenue paths.
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Models Depreciate Fast
- Frontier models are rapidly depreciating assets that lose commercial value quickly after newer models arrive.
- Short model lifespans mean R&D must be recouped faster or subsidized by investors.
Scale To Unlock New Capabilities
- Prioritize scale to unlock capability-driven markets rather than chasing short-term profit.
- Invest in large training runs because scale often yields new capabilities and revenue opportunities.
Use Ads To Signal Profitability Path
- Consider ads as a lever to demonstrate a path to profitability to investors even if not core strategy.
- Use ads to expand market and signal revenue potential while you pursue longer-term ambitions.