人工智能产业的快速扩张掩盖了其商业生态中的深层矛盾。2026年3月，全球单周Token调用量达到20.4万亿，中国日均调用量突破140万亿，较2024年初增长超过千倍[1]。然而这种惊人的使用量增长并未转化为均衡的利润分布。芯片层在生成式AI生态年化收入约4000亿美元的规模中独占约七成收入和近八成毛利，而应用层收入仅约600亿美元、毛利率多数徘徊在0%-30%的低位[1]。这种失衡反映了AI行业面临的第一个悖论：成本下降与账单反增的错位。
GPT-4的Token价格三年内下跌超过95%，从2023年3月的输入30美元/百万、输出60美元/百万大幅下降[1]。尽管单位成本急剧下落，企业和用户的总支出却在增加，形成了"越便宜越贵"的怪象。
敢于承担结果责任的厂商获利能力凸显。OpenAI的年化收入从2023年的20亿美元增至2026年2月底的超过250亿美元[1]；Anthropic的年化收入在2024年12月约10亿美元的基础上，到2026年5月飙升至470亿美元以上，其推理基础设施毛利率也从38%提升至70%以上[1]。与之形成对比的是，企业对开源模型的支出占比从前年的19%降至今年的11%，转而投向闭源方案，表明市场对承诺结果的提供商更有信心[1]。
新型计费模式的出现则反映了行业的转变。Intercom推出的智能客服产品Fin采取按实际解决问题计费的模式，每单收费0.99美元，未解决问题则不收取费用[1]。这种结果导向的定价方式体现了技术方对自身能力的承诺。OpenRouter平台上，Anthropic虽只占Token份额的12%，却获得了金额份额的46%，进一步验证了高价值厂商的溢价能力[1]。
The artificial intelligence sector is experiencing a fundamental disconnect between unit economics and overall profitability, according to analysis of market trends through mid-2026. As token prices have collapsed by over 95% since March 2023—dropping from $30 per million input tokens and $60 per million output tokens—the industry paradoxically faces rising total customer expenditures[1]. Global weekly token invocations reached 20.4 trillion in March 2026, while China's daily token consumption surged to 140 trillion, representing growth exceeding 1,000% from early 2024[1].
The generative AI ecosystem illustrates a striking concentration of value capture. With approximately $400 billion in annualized revenue across the sector, chip manufacturers capture roughly 70% of total revenue and nearly 80% of gross margins, leaving application-layer companies to divide approximately $60 billion in revenue with profit margins typically ranging from 0% to 30%[1]. This structural imbalance reflects what analysts term a "hierarchy paradox," where despite rapid value creation at application levels, capital flows persistently toward infrastructure layers. Anthropic exemplifies this dynamic, growing annualized recurring revenue from approximately $1 billion in December 2024 to over $47 billion by May 2026, with reasoning infrastructure gross margins expanding from 38% to above 70% during the same period[1]. OpenAI's trajectory similarly demonstrates infrastructure's gravitational pull on profits: the company achieved $2 billion in annualized revenue in 2023, $6 billion in 2024, exceeding $20 billion in 2025, and surpassing $25 billion by February 2026, though free cash flow profitability remains projected for approximately 2030[1].
A fourth emerging paradox involves the divergence between open-source adoption and monetization. Enterprise spending on open-source models declined from 19% of AI spending budgets to 11%, while closed-source captured 89% of expenditures[1]. On the OpenRouter platform, Anthropic commands 46% of transaction value despite representing only 12% of token volume, underscoring how proprietary solutions extract disproportionate revenue[1]. New result-based pricing models are also emerging, exemplified by Intercom's Fin product, which charges $0.99 per successfully resolved customer issue, with no fee charged when problems remain unresolved[1].