AI Markets: Deep Dive with a16z's David George

章节 1：AI 市场概览与财务效率新指标

📝 本节摘要：

David George 首先阐述了发布这份深度报告的初衷，指出 AI 市场目前“需求侧极其疯狂”，且行业仍处于 10-15 年长周期的极早期阶段。通过分析大量内部数据，他发现 2025 年迎来了收入增长的全面加速，顶级 AI 公司达到 1 亿美元收入里程碑的速度远超 SaaS 时代，且在销售和营销（S&M）上的支出更低。在财务指标上，尽管 AI 公司的毛利率（Gross Margins）因推理成本略低，但这被视为产品被高频使用的“荣誉勋章”。最后，他引入了一个关键的新效率指标——人均 ARR（ARR per FTE），数据显示顶级 AI 公司的这一指标高达 50-100 万美元，显著优于 SaaS 时代的 40 万美元基准。

[原文] [David George]: let me just start with what I think the big takeaways are from this piece because this is the first time we've ever done this style piece We produce so much work and so much analysis It's like exhaust uh in you know inside of our team and we thought you know we have so many different thoughts and and points of view Why don't we put them on paper and share them out with the world So that was the genesis of this

[译文] [David George]: 让我先从我认为这篇文章的主要结论开始说起，因为这是我们第一次做这种风格的内容。我们在团队内部产出了大量的工作成果和分析报告，就像是某种“副产品”一样。所以我们想，既然我们有这么多不同的想法和观点，为什么不把它们写下来并与全世界分享呢？这就是这件事的缘起。

[原文] [David George]: My big takeaways from doing this one you know AI demand side is crazy The actual uptake growth quality of companies in AI is extremely encouraging from our standpoint Companies are starting to run themselves better I'm going to show you some stats on that that you know there's been some sort of X buzz uh including this morning You know kind of debating what's going on there But this crop of companies I would say is more impressive uh than than prior crops of companies partially because the demand for their products is so high Um that's demand side Supply side is healthy right now

[译文] [David George]: 我做这份报告得出的主要结论是，你知道，AI 的需求侧非常疯狂。从我们的角度来看，AI 公司的实际采用率、增长和质量都非常令人鼓舞。公司开始更好地管理自己。我会向你们展示一些相关的统计数据，你知道最近在 X（推特）上有一些讨论，包括今天早上，大家在辩论到底发生了什么。但我会说，这一批公司比之前的任何一批公司都更令人印象深刻，部分原因是市场对它们产品的需求太高了。那是需求侧，供给侧目前也很健康。

[原文] [David George]: And then lastly my big conclusion what has me so excited about where we are now is just how early we are in this product cycle Um you know product cycles drive our business And you know these are 10 15 year cycles and we're just at the very beginning of it right now

[译文] [David George]: 最后，我的主要结论——也是让我对现状感到如此兴奋的原因——就是我们目前正处于这个产品周期的非常早期阶段。你知道，产品周期驱动着我们的业务。这些通常是 10 到 15 年的周期，而我们要现在才刚刚开始。

[原文] [David George]: So let's dive in We invest across all private stages This is a chart that just shows our activity We're very busy It's across all verticals We on the growth side have been most active in AI and infer apps uh and then in in AD but also very active in our other verticals um as well

[译文] [David George]: 让我们深入探讨一下。我们投资覆盖了所有私募阶段。这张图展示了我们的活动情况，我们非常忙碌。投资跨越了所有垂直领域。在成长型投资方面，我们在 AI、推理应用（Infra Apps）以及 AD（航空航天/国防）领域最为活跃，但在其他垂直领域也非常活跃。

[原文] [David George]: Anyway here's some data So we collect tons and tons of data as a growth team because we're basically seeing every growth stage company in the market uh as a either portfolio company or as a prospect And so we have a great data analysis team We did some data analysis I think this stuff is just super interesting We geek out on it To me the big conclusion from this is 2025 was a year for accelerated revenue growth Um you know revenue obviously slowed you know in 2022 23 24 following the rate hikes and and the pullback in some of the tech stuff But 2025 reversed that trend

[译文] [David George]: 无论如何，来看一些数据。作为成长型投资团队，我们收集了海量数据，因为我们基本上看过了市场上每一家成长期公司，无论是作为被投公司还是潜在投资对象。我们有一个很棒的数据分析团队，做了一些分析。我觉得这些东西超级有趣，我们对此很狂热。对我来说，得出的主要结论是：2025 年是收入加速增长的一年。你知道，随着加息和科技股的回调，收入增速在 2022、2023 和 2024 年显然放缓了。但 2025 年扭转了这一趋势。

[原文] [David George]: the fastest growing AI companies are reaching 100 million bucks of revenue significantly faster than the fastest growing SAS companies in their era And there's a really important thing I want to call out about why that is the case and that is because end customer demand is so strong and the products are so compelling It's not because they spend more money on sales and marketing It's actually the opposite The the best AI companies that are growing the fastest are not the ones spending the most amount of money on sales and marketing and they're spending less money on sales and marketing than their SAS counterparts And yet they're growing much much faster

[译文] [David George]: 增长最快的 AI 公司达到 1 亿美元收入的速度，明显快于那个时代增长最快的 SaaS 公司。我想特别指出一件非常重要的事来解释为什么会这样，那就是因为终端客户的需求太强劲了，而且产品太具吸引力了。这并不是因为它们在销售和营销（Sales and Marketing）上花了更多的钱。实际上恰恰相反。那些增长最快的顶级 AI 公司并不是在销售和营销上花钱最多的，它们花的钱比当年的 SaaS 同行要少，但它们的增长速度却要快得多。

[原文] [David George]: Roughly speaking the AI companies are growing two and a half times plus faster than the non-AI companies And that shouldn't be a huge surprise The best of the AI companies are growing very very fast We had to triple check this data when we saw the you know the the AI top you know top performers growing 693% year-over-year um but it matches up our experience you know and and anecdotes that we see from the portfolio companies

[译文] [David George]: 粗略地说，AI 公司的增长速度是非 AI 公司的 2.5 倍以上。这不应该太令人惊讶。最好的 AI 公司增长得非常非常快。当我们看到顶级 AI 表现者实现了 693% 的同比增长时，我们不得不反复核实了三遍数据，但这与我们的经验以及我们在被投公司中看到的轶事是相符的。

[原文] [David George]: This is the margin profile uh that we're seeing in the data set... Gross margins are a little bit worse for AI companies Um you've probably heard us talk about this before but in a way we feel like low gross margins for AI companies are sort of a badge of honor in the sense that we want to see if if if if low gross margins are a result of high inference costs one that means people are using AI features and two we have a belief that those inference costs over time are going to come down Uh so in an odd way if we see an AI pitch and the gross margins are super high we're a little bit skeptical because that may mean that the AI features are not actually what is being bought uh or used by the customers

[译文] [David George]: 这是我们在数据集中看到的利润率概况……AI 公司的毛利率（Gross Margins）略差一些。你可能以前听我们谈过这个，但在某种程度上，我们觉得 AI 公司的低毛利率就像是一种“荣誉勋章”。因为如果低毛利率是由高推理成本（Inference Costs）导致的：第一，这意味着人们确实在使用 AI 功能；第二，我们相信这些推理成本随着时间的推移会降下来。所以奇怪的是，如果我们看到一个 AI 项目的推介，其毛利率超高，我们会有点怀疑，因为这可能意味着客户购买或使用的实际上并不是 AI 功能。

[原文] [David George]: We're going to talk about AR per FTE but this is a new thing that we've started focusing on and this is one of the things that got a lot of pickup and discussion uh on X in the last few days ARR per FTE is sort of a measure of the efficiency of how you run your company in general So it encapsulates all of your costs Uh it encapsulates you know not just your sales and marketing which is an efficiency measure that we've always kind of looked at when we do analysis in the past but it also captures your overhead It captures your R&D

[译文] [David George]: 我们要谈谈“人均 ARR”（ARR per FTE），这是我们开始关注的一个新指标，也是过去几天在 X 上引起大量关注和讨论的话题之一。ARR per FTE 某种程度上是衡量你公司整体运营效率的指标。所以它涵盖了你所有的成本。它不仅涵盖了销售和营销——这是我们在过去的分析中一直关注的效率指标——而且还涵盖了你的管理费用（Overhead）和研发费用（R&D）。

[原文] [David George]: Uh and so for the best AI companies they're running at like 500,000 to a million dollars uh per per FTE And the rule of thumb for previous software businesses in the SAS era was like $400,000 in the last generation Again I'm going to talk about this a little bit more but the reason why this is the case is mostly because demand is very very strong for their products Um you know and so they need a less resource to go take it to market

[译文] [David George]: 对于最好的 AI 公司来说，它们的人均产出大约是 50 万到 100 万美元。而在上一代 SaaS 时代的软件企业，其经验法则是大概 40 万美元。我要再次多说一点，之所以会出现这种情况，主要是因为对其产品的需求非常非常强劲，所以它们推向市场所需的资源更少。

[原文] [Host]: David maybe a quick clarifying just before we we um go to this slide here So how do we how do you define AI companies Is that defined as postjack GBT versus historical AI ML companies founded by a certain time period

[译文] [Host]: David，在我们进入这张幻灯片之前，也许可以快速澄清一下。你们是如何定义“AI 公司”的？是定义为 ChatGPT 之后的公司，还是某个特定时期成立的历史性 AI/ML 公司？

[原文] [David George]: Yeah Yeah it's sort of post postg and and some of them have were founded like right around that time We'd give a little bit of grace but but if they're their first product in market was an AI you know native product then that's how we define it

[译文] [David George]: 对，是的，差不多就是“后 ChatGPT”时代。其中一些公司可能就在那个时间点前后成立，我们会给一点宽限期。但只要它们推向市场的第一个产品是 AI 原生（AI Native）产品，那就是我们的定义标准。