Caerus Alpha
    Briefing Note · Enterprise AI Economics
    The Cost Economics of
    Generative AI in the Enterprise
    Five structural trends reshaping how enterprises budget, build, and buy AI capabilities — with data visualizations for each. Analysis by Caerus Alpha Research.
    Trend 01·Inference Deflation
    Token costs fell 50× in three years — not gradually, but in lurches, each triggered by a model release that made the previous pricing regime look absurd.
    Enterprises that locked infrastructure contracts in 2022 are paying ten times the current market rate for equivalent capability. The implication is structural: inference cost is no longer a variable to optimize around. It is a floor, and the floor is dropping. The correct response is not to find cheaper compute — it is to rebuild the financial model from the current floor upward, and to treat any contract signed before 2024 as a liability under review.
    Inference Cost Has Collapsed 50× in Three Years
    Cost per million tokens (USD, log scale) — frontier, mid-tier, and small models, 2022–2025
    Source: OpenAI, Anthropic, Google, Mistral published pricing; analyst estimates. Frontier model costs fell from ~$60/M tokens in 2022 to under $2 today — a pace that structurally alters enterprise unit economics and makes 2022-era infrastructure contracts a liability.
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    Data represents synthesized estimates from public sources; not investment advice.