原文地址: https://www.growthunhinged.com/p/how-ai-apps-make-money
In the past few years there has been an explosion of AI products and applications—in fact, AI products already attract more than one-fifth of all VC funding.
近年来，人工智能产品的数量和应用呈现井喷式增长——实际上，AI产品已吸引了超过五分之一的风险资本投资。
Many of these AI apps change our relationship with software from something that makes us more productive to something that generates entirely new work products. This makes for favorable market conditions to create new innovative pricing strategies, which leaves us wondering: how are AI apps making money?
许多人工智能应用将我们的软件体验从提升效率的工具转变为创造全新工作价值的平台。这一转变催生了有利的市场环境，孕育出创新的定价策略，让人不禁思考：这些AI应用究竟是如何盈利的？
In the Large Language Model (LLM) space and the infrastructure layer, usage-based pricing models have been the norm since commercialization. Most of the companies charge on a per token basis, which is closely aligned with the cost of compute. We instead investigated 40 leading AI-native companies in the application layer to see what’s happening on the pricing front.
在大型语言模型领域及基础设施层面，商业化以来普遍采用基于使用量的定价模式。多数公司按令牌计费，与计算成本息息相关。我们考察了40家人工智能驱动的应用层领先企业，以揭示其定价策略的新动向。
You can see a simplified version of the different AI layers. The focus of this article is on the top layer — the native AI applications.
你可以观察到人工智能各层次的一个简化模型，本文聚焦于顶层——即本土化人工智能应用。
The primary criteria used to select the companies was based on external funding and traction from public sources like the Forbes AI 50 List and Sequoia’s Generative AI market map. The 40 companies include marketing tools (ex: Jasper, Copy.ai), productivity apps (ex: Tome, Glean), vertical specific products (ex: Harvey, Co:Helm), and others (ex: Synthesia, HeyGen).
公司入选的主要标准是其外部融资情况和市场影响力，参考了如《福布斯》AI 50强榜单及红杉资本的生成式AI市场报告等公信力高的资源。这40家企业包括营销工具（如Jasper和Copy.ai）、提升效率的应用（如Tome和Glean）、特定行业的解决方案（如Harvey和Co:Helm），以及其它项目（如Synthesia和HeyGen）。
Specifically, we reviewed public data focused around pricing models, value metrics, packaging, free versions and pricing transparency. We deliberately focused on AI-native apps rather than incumbents since these startups don’t have the baggage of a prior install base or legacy pricing model.
我们特别考察了有关定价策略、价值标准、产品包装、免费版本及价格透明度的公开数据。我们专注于人工智能初创企业，因其未受既有用户基数和传统定价模式的束缚。