Menlo Ventures 发布 2026 企业级 AI 应用报告：部署支出达 1770 亿美元
Menlo Ventures 这份企业 AI 报告数据很硬：部署支出涨到 1770 亿美元，Claude Code 加 Codex 吃下编程市场 70%，Kimi 拿走开源支出的 61%，花几分钟看看行业格局变化。
Menlo Ventures 发布《2026: The State of Enterprise AI》报告，企业 AI 部署支出从 2025 年的 330 亿美元增至 2026 年 9 月的 1770 亿美元，增长 5.4 倍，相当于公共云收入的 30% 以上。Anthropic、OpenAI 和 Google 拿走其中 69%、约 1230 亿美元，Anthropic 在企业 API 支出中的份额从 40% 升至 55%。编程和聊天机器人占 773 亿美元应用市场的 76%，其中 Claude Code 与 Codex 合计拿下 340 亿美元编程市场的 70%。开源模型处理 19% 的 token 但只占 4% 的支出，中国模型占开源支出的 89%，其中 Kimi 占 61%。前沿模型支出份额从 35% 升至 63%，热门模型转向价格更高的 Claude Opus 5.5 和 GPT-6 Astra。
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.
