Bayes and Base Rates: How History Can Guide Our Assessment of the Future

Feb 10, 2026

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The ongoing massive investments in artificial intelligence (AI) aim to satisfy a huge increase in anticipated demand, which in turn has led some firms to offer rosy growth forecasts.
To assess these forecasts, investors may apply Bayes' Theorem by starting with an initial belief and updating it as new results appear. Base rates are a sensible start for initial beliefs.
The base rates for U.S. public companies over 75 years suggest OpenAI and Oracle Cloud have a low probability of meeting their five-year revenue projections. Offsetting this are data showing rapid diffusion of AI, which signals major demand and short-term growth.
A large database of projects shows less than 10 percent are completed on time and on budget, which should temper overly optimistic expectations for the buildout of AI infrastructure.
Companies sometimes pursue a preemptive strategy in which they announce big capacity commitments to deter competitors and entrants from investing.

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Bayes and Base Rates: How History Can Guide Our Assessment of the Future

Large investments in artificial intelligence (AI) aim to meet anticipated demand, which has led some firms to give rosy forecasts. To assess them, investors may apply Bayes’ Theorem by starting with an initial belief and updating it. Base rates are a useful prior. The base rates for U.S. companies suggest OpenAI and Oracle Cloud have low odds of meeting their sales projections, even if the diffusion of AI signals major demand. A database of big projects shows few are done on time and budget.

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