Menlo 报告：企业 AI 支出 5.4 倍，Astra 成主流贵价模型

Rohan Paul @rohanpaul_ai原推发布于 2026.11.04

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A solid study from @MenloVentures "2026: The State of Enterprise AI" > Enterprise AI deployment spend jumped from $33B in 2025 to $177B by Sept-2026, a 5.4x rise that beat the prior year’s 3.9x growth and now equals over 30% of public cloud revenue. > Agents drove the jump: on OpenRouter, agent traffic passed human traffic on Feb-2026, then grew 37x versus 5x for humans, reaching 80% of tokens, or 131T per week. > Companies budgeted 1.9x their 2025 AI spend but averaged 4.7x, since parallel agents scale spending with work rather than headcount; the median reached only 2.2x, so a few power users drive a disproportionate share. > Anthropic, OpenAI and Google took 69% of deployment dollars, $123B, up from 50%; Anthropic’s share of enterprise API spend rose from 40% to 55%, OpenAI’s from 27% to 31%, Google’s fell from 21% to 9%. > Buyers keep paying for capability: frontier models’ spend share rose from 35% to 63%, and the most popular models shifted from Claude Sonnet 4.5 and GPT-5 to pricier Claude Opus 5.5 and GPT-6 Astra. > Enterprises spend $1.70 using AI for every $1 spent building models, $177B versus $102.5B, and Anthropic and OpenAI alone account for an estimated 25%+ of AWS, Azure and Google Cloud revenue. > Coding and chatbots make up 76% of the $77.3B app market, since compilers and tests let agents verify results; coding hit $34.0B, with Claude Code and Codex taking $24.0B, or 70%. > Open-source handles 19% of tokens, up from 11%, but only 4% of spend, as its average price fell 3.3x to $0.13 per million; Chinese models take 89% of open-source spend, led by Kimi at 61%. > AI is expanding software budgets: 55% of incremental AI spend came from new budgets, and only 9%, or $12.6B, shifted from software to AI-native vendors, trimming application SaaS growth from 13% to 11%. > AI-native providers took 77% of application spend, up from 63%, and 96% of coding, but incumbents hold IT at 91% and HR at 68%, where AI must fit existing systems of record.