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Sarah Gwilliam is neither a software engineer nor—by her own admission— someone who “speaks AI”. But after her father died recently she got the spark of an idea for creating a generative artificial-intelligence startup that would help others like her handle their grief and sort out their late loved ones’ affairs. Call it wedding planning for funerals.
Her firm, Solace, is still more of an early-stage startup than an established business. But apart from herself, almost no human being is helping her build it. She has joined an AI-powered incubator, called Audos, which decided that her idea was promising. Its bots helped to set her up online and on Instagram. If her idea works out, the incubator will not only provide capital; its AI agents will support Ms Gwilliam with product development, sales, marketing and back-office work, all in exchange for a royalty. She does not need staff. In effect, AI helped her co-found the company. “I can’t tell you how empowering it was,” she says.
As is its custom, Silicon Valley has already coined a neologism that describes single founders like Ms Gwilliam: they are “solopreneurs”. In tech circles, there are bets on which of them is likely to create the first single- person unicorn—an unlisted firm worth more than $1bn. Some hope that generative AI will make starting a business so cheap and hassle-free that anyone will be able to become an entrepreneur much as anyone can become a YouTuber—a breath of fresh air in America’s concentrated business landscape. Whether people like Ms Gwilliam will be able to escape the suffocating grip of the tech giants, however, is another matter. Technological revolutions have a habit of shaking up the way firms do business. The increased importance of machinery combined with the expansion of transport networks in the late 19th century led to the rise of giant corporations. Ronald Coase, a British economist, argued in his 1937 paper “The Nature of the Firm” that their existence was a testament to the efficiency of consolidating and managing work within the confines of a business, rather than outsourcing activities to the market. That, however, began to change thanks to digital communication. Not only could companies more easily outsource manufacturing and back-office jobs to low-cost countries. They could also rely on internet platforms like Google for marketing and Amazon Web Services for computing.
The rise of AI could well accelerate the trend, as semi-autonomous agents provided by Silicon Valley enable firms to perform the same amount of work with fewer employees. Henrik Werdelin, who co-founded Audos, says that the rise of cloud computing helped him start several new businesses over the past 20 years or so with little more than the swipe of a credit card to get going. He describes AI as the next wave in that “democratisation”. “You don’t need to code, you don’t need to be able to use Photoshop, because you can get AI to help with that.” This, he hopes, will give rise to a flood of startups built by people like Ms Gwilliam with no background in technology but who have identified real problems to solve.
Another evangelist is Karim Lakhani of Harvard Business School. It now offers a leadership course for executives in which they use generative AI to build a snack-food company in 90 minutes, using the technology to perform customer research, generate recipes, find suppliers and design packaging. In a recent paper, Mr Lakhani and his co-authors presented a field trial in which 776 professionals at Procter & Gamble, a consumer-goods company, were asked to address a real business need either individually or in two- person teams, with and without using generative-AI tools. It found that AI significantly boosted performance, helping individuals with AI match the performance of teams without it. AI proved to be more of a “teammate” than a tool.
With the era of free money over, entrepreneurs are eager to find ways to keep costs down. Peter Walker of Carta, which helps startups manage equity ownership, says that founders used to boast about how many employees they had. “Now it’s a badge of honour to say, ‘look how few people work for me’.” According to Carta’s data, the typical period it takes founders to hire their first employee after their startup incorporates has risen from less than six months in 2022 to more than nine months in 2024 (see chart). Base44, an AI coding startup, was recently sold to Wix, a web-development platform, for $80m. It had just eight employees.
It is early days, of course. For one thing, AI agents are far from foolproof. In June Anthropic, an AI lab, revealed the results of an experiment in which its Claude Sonnet model operated a vending machine at the firm’s headquarters. The bot’s goal was to avoid bankruptcy. It was good at identifying suppliers and adapting to user requests (including hunting for a tungsten cube mischievously requested by one employee). But it ignored lucrative opportunities, hallucinated, offered too many discounts and ultimately failed to make money.
Other forces may also get in the way of an AI-infused surge in entrepreneurship. Despite the growth of the internet, social media, software- as-a-service and cloud computing over recent decades, business formation in America was anaemic until the pandemic—the result in part of an ageing population. That demographic pressure will only intensify.
For all the promise of generative AI, it poses problems for entrepreneurs, too. Annabelle Gawer of the University of Surrey notes that although the technology lowers barriers to entry for new businesses, it also makes it easier to quickly copy ideas. Unless a founder has unique expertise in their domain, that may make it harder to sustain a competitive advantage. Moreover, the provision of AI tools is dominated by tech giants and the labs they invest in, such as OpenAI, backed by Microsoft, and Anthropic, backed by Amazon and Google. Ms Gawer draws an analogy with the rise of cloud computing in the 2010s, which those three tech giants dominate. Although that infrastructure has made life easier for startups, it has also left them dependent on the cloud triumvirate, which has been able to capture a good share of the value these firms have generated. Last year the trio’s net profits were equivalent to 7% of America’s total, up from 2% a decade before. Another possibility is that the tech giants could pinch smaller companies’ best ideas. For now, Ms Gwilliam of Solace is sanguine. What she calls “first-mover disadvantage” could be “a bummer”, but it could also validate her idea. “Maybe they’ll come to me and say, ‘We want Solace.’ And then I’ll be, like, ‘Great, sold!’” Just like a typical entrepreneur, then.
莎拉·吉廉（Sarah Gwilliam）对编程一窍不通，甚至自嘲不是个“懂AI的人”。但不久前，父亲的离世让她萌生了一个创业想法：用生成式人工智能（AI）来帮助像她一样的人，在悲痛中处理逝去亲人的身后事。你可以把它理解为“葬礼版的婚礼策划”。
她的公司，Solace，尚在襁褓，羽翼未丰。但除了她自己，公司的创建过程几乎没有第二个人的身影。她加入了一个名为Audos的人工智能孵化器，后者认为她的想法大有可为。孵化器的AI机器人帮她搭建了网站、开通了Instagram账号。如果项目进展顺利，孵化器不仅会提供资金，其麾下的AI“员工”们还将全面接手产品开发、销售、市场营销和后台行政工作，以此换取一笔授权费。莎拉根本不需要雇佣任何员工。可以说，AI就是她的联合创始人。“那种赋能的感觉，简直难以言表。”她感叹道。
硅谷向来擅长创造新词，一个用以形容莎拉这类创始人的词汇已经诞生了：“独行创业者” (solopreneurs)。在科技圈，人们甚至开始下注，赌谁会成为第一个缔造“一人独角兽”——即估值超过10亿美元的未上市公司——的人。有人期望，生成式AI能让创业的门槛变得足够低、流程变得足够简单，以至于任何人都能像成为一名视频博主（YouTuber）那样轻松地开创自己的事业，为高度集中的美国商业版图注入一股清流。然而，像莎拉这样的人能否最终逃出科技巨头们的“五指山”，还是个未知数。
每一次技术革命，都会彻底颠覆商业世界的游戏规则。19世纪末，机器的重要性日益凸显，加上交通网络的扩张，催生了巨无霸式的现代企业。英国经济学家罗纳德·科斯（Ronald Coase）在其1937年的论文《企业的性质》中指出，将工作整合在一家企业内部进行管理，远比将所有业务外包给市场要高效得多，这便是大企业存在的根本原因。然而，数字通信的出现开始改变这一切。企业不仅能更轻易地将制造业和行政工作外包给低成本国家，还可以依赖谷歌这样的互联网平台做营销，借助亚马逊云服务（AWS）满足算力需求。
人工智能的崛起，无疑将加速这一趋势。由硅谷提供的半自主AI代理，能让企业用更少的人完成同样多的工作。Audos的联合创始人亨里克·韦德林（Henrik Werdelin）表示，在过去二十年里，云计算的兴起让他只需刷一下信用卡，就能轻松启动好几个新项目。他将AI形容为这股“创业民主化”浪潮中的下一次巨浪。“你不需要会写代码，也不需要会用Photoshop，因为AI能帮你搞定这一切。”他希望，这将催生出一大批由莎拉这样的人所创办的公司——他们没有技术背景，却发现了真实存在、亟待解决的问题。
哈佛商学院的卡里姆·拉哈尼（Karim Lakhani）是另一位摇旗呐喊者。哈佛商学院如今开设了一门高管领导力课程，学员们可以在90分钟内，利用生成式AI从零到一创建一家零食公司，用技术完成客户调研、生成配方、寻找供应商和设计包装等全部流程。在最近的一篇论文中，拉哈尼和他的同事们公布了一项实地试验结果：他们让消费品巨头宝洁公司（Procter & Gamble）的776名专业人士，以单人或两人小组的形式，分别在“使用”和“不使用”生成式AI工具的情况下，去解决一个真实的业务难题。研究发现，AI显著提升了工作表现，单人借助AI的成果，足以媲美没有AI的两人团队。AI的角色，与其说是一个工具，不如说是一个“队友”。
低息借贷的时代已经一去不复返，创业者们正想方设法地压缩成本。帮助初创公司管理股权的平台Carta的彼得·沃克（Peter Walker）说，过去，创始人们喜欢吹嘘自己公司有多少员工，“而现在，‘看我的人多精简’反而成了一种荣誉勋章。”根据Carta的数据，初创公司从注册成立到雇佣第一名员工的平均时长，已从2022年的不足6个月，延长到了2024年的超过9个月。AI编程初创公司Base44最近被网站开发平台Wix以8000万美元的价格收购，而它仅仅只有8名员工。
当然，一切才刚刚开始。一方面，AI代理远非万无一失。今年6月，人工智能实验室Anthropic公布了一项实验结果，他们让其Claude Sonnet模型去运营公司总部的一台自动售货机。机器人的目标是避免亏损。它很擅长识别供应商、适应用户需求（甚至为了一名员工恶作剧般的要求，去寻找一块钨立方），但它却忽略了高利润的机会，出现了“幻觉”，提供了过多的折扣，最终没能赚到钱。
另一方面，其他因素也可能阻碍AI驱动下的创业热潮。尽管过去几十年里，互联网、社交媒体、软件即服务（SaaS）和云计算发展迅猛，但在疫情之前，由于人口老龄化等原因，美国的新企业成立数量一直增长乏力。这一人口结构带来的压力只会越来越大。
尽管生成式AI前景光明，但它也给创业者带来了新的难题。萨里大学的安娜贝尔·加维尔（Annabelle Gawer）指出，这项技术虽然降低了新业务的准入门槛，却也让复制创意变得轻而易举。除非创始人在自己的领域拥有独一无二的专业知识，否则可能很难维持竞争优势。
更重要的是，AI工具的供应，被科技巨头及其投资的实验室牢牢掌控着，例如微软支持的OpenAI，以及亚马逊和谷歌投资的Anthropic。加维尔女士将其与2010年代云计算的崛起相类比，当时的市场同样由这三家科技巨头主导。尽管云基础设施让初创公司的日子好过了许多，但也让它们对这个“三巨头联盟”产生了依赖，后者也因此攫取了这些初创公司所创造价值的相当一部分。去年，这三家巨头的净利润相当于美国企业总利润的7%，而十年前这个数字仅为2%。另一种可能是，科技巨头们会直接“借鉴”小公司的绝佳创意。 不过眼下，Solace公司的莎拉·吉廉对此倒是颇为乐观。她所说的“先发劣势”或许会“有点扫兴”，但也恰恰能验证她想法的价值。“也许他们（巨头）会找上门来说，‘我们想要Solace’。那我就会回答，‘太好了，卖给你！’” 看，这不就是一个典型的创业者心态么。
Sarah Gwilliam is neither a software engineer nor—by her own admission— someone who “speaks AI”. But after her father died recently she got the spark of an idea for creating a generative artificial-intelligence startup that would help others like her handle their grief and sort out their late loved ones’ affairs. Call it wedding planning for funerals.
Her firm, Solace, is still more of an early-stage startup than an established business. But apart from herself, almost no human being is helping her build it. She has joined an AI-powered incubator, called Audos, which decided that her idea was promising. Its bots helped to set her up online and on Instagram. If her idea works out, the incubator will not only provide capital; its AI agents will support Ms Gwilliam with product development, sales, marketing and back-office work, all in exchange for a royalty. She does not need staff. In effect, AI helped her co-found the company. “I can’t tell you how empowering it was,” she says.
As is its custom, Silicon Valley has already coined a neologism that describes single founders like Ms Gwilliam: they are “solopreneurs”. In tech circles, there are bets on which of them is likely to create the first single- person unicorn—an unlisted firm worth more than $1bn. Some hope that generative AI will make starting a business so cheap and hassle-free that anyone will be able to become an entrepreneur much as anyone can become a YouTuber—a breath of fresh air in America’s concentrated business landscape. Whether people like Ms Gwilliam will be able to escape the suffocating grip of the tech giants, however, is another matter. Technological revolutions have a habit of shaking up the way firms do business. The increased importance of machinery combined with the expansion of transport networks in the late 19th century led to the rise of giant corporations. Ronald Coase, a British economist, argued in his 1937 paper “The Nature of the Firm” that their existence was a testament to the efficiency of consolidating and managing work within the confines of a business, rather than outsourcing activities to the market. That, however, began to change thanks to digital communication. Not only could companies more easily outsource manufacturing and back-office jobs to low-cost countries. They could also rely on internet platforms like Google for marketing and Amazon Web Services for computing.
The rise of AI could well accelerate the trend, as semi-autonomous agents provided by Silicon Valley enable firms to perform the same amount of work with fewer employees. Henrik Werdelin, who co-founded Audos, says that the rise of cloud computing helped him start several new businesses over the past 20 years or so with little more than the swipe of a credit card to get going. He describes AI as the next wave in that “democratisation”. “You don’t need to code, you don’t need to be able to use Photoshop, because you can get AI to help with that.” This, he hopes, will give rise to a flood of startups built by people like Ms Gwilliam with no background in technology but who have identified real problems to solve.
Another evangelist is Karim Lakhani of Harvard Business School. It now offers a leadership course for executives in which they use generative AI to build a snack-food company in 90 minutes, using the technology to perform customer research, generate recipes, find suppliers and design packaging. In a recent paper, Mr Lakhani and his co-authors presented a field trial in which 776 professionals at Procter & Gamble, a consumer-goods company, were asked to address a real business need either individually or in two- person teams, with and without using generative-AI tools. It found that AI significantly boosted performance, helping individuals with AI match the performance of teams without it. AI proved to be more of a “teammate” than a tool.
With the era of free money over, entrepreneurs are eager to find ways to keep costs down. Peter Walker of Carta, which helps startups manage equity ownership, says that founders used to boast about how many employees they had. “Now it’s a badge of honour to say, ‘look how few people work for me’.” According to Carta’s data, the typical period it takes founders to hire their first employee after their startup incorporates has risen from less than six months in 2022 to more than nine months in 2024 (see chart). Base44, an AI coding startup, was recently sold to Wix, a web-development platform, for $80m. It had just eight employees.
It is early days, of course. For one thing, AI agents are far from foolproof. In June Anthropic, an AI lab, revealed the results of an experiment in which its Claude Sonnet model operated a vending machine at the firm’s headquarters. The bot’s goal was to avoid bankruptcy. It was good at identifying suppliers and adapting to user requests (including hunting for a tungsten cube mischievously requested by one employee). But it ignored lucrative opportunities, hallucinated, offered too many discounts and ultimately failed to make money.
Other forces may also get in the way of an AI-infused surge in entrepreneurship. Despite the growth of the internet, social media, software- as-a-service and cloud computing over recent decades, business formation in America was anaemic until the pandemic—the result in part of an ageing population. That demographic pressure will only intensify.
For all the promise of generative AI, it poses problems for entrepreneurs, too. Annabelle Gawer of the University of Surrey notes that although the technology lowers barriers to entry for new businesses, it also makes it easier to quickly copy ideas. Unless a founder has unique expertise in their domain, that may make it harder to sustain a competitive advantage. Moreover, the provision of AI tools is dominated by tech giants and the labs they invest in, such as OpenAI, backed by Microsoft, and Anthropic, backed by Amazon and Google. Ms Gawer draws an analogy with the rise of cloud computing in the 2010s, which those three tech giants dominate. Although that infrastructure has made life easier for startups, it has also left them dependent on the cloud triumvirate, which has been able to capture a good share of the value these firms have generated. Last year the trio’s net profits were equivalent to 7% of America’s total, up from 2% a decade before. Another possibility is that the tech giants could pinch smaller companies’ best ideas. For now, Ms Gwilliam of Solace is sanguine. What she calls “first-mover disadvantage” could be “a bummer”, but it could also validate her idea. “Maybe they’ll come to me and say, ‘We want Solace.’ And then I’ll be, like, ‘Great, sold!’” Just like a typical entrepreneur, then.
莎拉·吉廉（Sarah Gwilliam）对编程一窍不通，甚至自嘲不是个“懂AI的人”。但不久前，父亲的离世让她萌生了一个创业想法：用生成式人工智能（AI）来帮助像她一样的人，在悲痛中处理逝去亲人的身后事。你可以把它理解为“葬礼版的婚礼策划”。
她的公司，Solace，尚在襁褓，羽翼未丰。但除了她自己，公司的创建过程几乎没有第二个人的身影。她加入了一个名为Audos的人工智能孵化器，后者认为她的想法大有可为。孵化器的AI机器人帮她搭建了网站、开通了Instagram账号。如果项目进展顺利，孵化器不仅会提供资金，其麾下的AI“员工”们还将全面接手产品开发、销售、市场营销和后台行政工作，以此换取一笔授权费。莎拉根本不需要雇佣任何员工。可以说，AI就是她的联合创始人。“那种赋能的感觉，简直难以言表。”她感叹道。
硅谷向来擅长创造新词，一个用以形容莎拉这类创始人的词汇已经诞生了：“独行创业者” (solopreneurs)。在科技圈，人们甚至开始下注，赌谁会成为第一个缔造“一人独角兽”——即估值超过10亿美元的未上市公司——的人。有人期望，生成式AI能让创业的门槛变得足够低、流程变得足够简单，以至于任何人都能像成为一名视频博主（YouTuber）那样轻松地开创自己的事业，为高度集中的美国商业版图注入一股清流。然而，像莎拉这样的人能否最终逃出科技巨头们的“五指山”，还是个未知数。
每一次技术革命，都会彻底颠覆商业世界的游戏规则。19世纪末，机器的重要性日益凸显，加上交通网络的扩张，催生了巨无霸式的现代企业。英国经济学家罗纳德·科斯（Ronald Coase）在其1937年的论文《企业的性质》中指出，将工作整合在一家企业内部进行管理，远比将所有业务外包给市场要高效得多，这便是大企业存在的根本原因。然而，数字通信的出现开始改变这一切。企业不仅能更轻易地将制造业和行政工作外包给低成本国家，还可以依赖谷歌这样的互联网平台做营销，借助亚马逊云服务（AWS）满足算力需求。
人工智能的崛起，无疑将加速这一趋势。由硅谷提供的半自主AI代理，能让企业用更少的人完成同样多的工作。Audos的联合创始人亨里克·韦德林（Henrik Werdelin）表示，在过去二十年里，云计算的兴起让他只需刷一下信用卡，就能轻松启动好几个新项目。他将AI形容为这股“创业民主化”浪潮中的下一次巨浪。“你不需要会写代码，也不需要会用Photoshop，因为AI能帮你搞定这一切。”他希望，这将催生出一大批由莎拉这样的人所创办的公司——他们没有技术背景，却发现了真实存在、亟待解决的问题。
哈佛商学院的卡里姆·拉哈尼（Karim Lakhani）是另一位摇旗呐喊者。哈佛商学院如今开设了一门高管领导力课程，学员们可以在90分钟内，利用生成式AI从零到一创建一家零食公司，用技术完成客户调研、生成配方、寻找供应商和设计包装等全部流程。在最近的一篇论文中，拉哈尼和他的同事们公布了一项实地试验结果：他们让消费品巨头宝洁公司（Procter & Gamble）的776名专业人士，以单人或两人小组的形式，分别在“使用”和“不使用”生成式AI工具的情况下，去解决一个真实的业务难题。研究发现，AI显著提升了工作表现，单人借助AI的成果，足以媲美没有AI的两人团队。AI的角色，与其说是一个工具，不如说是一个“队友”。
低息借贷的时代已经一去不复返，创业者们正想方设法地压缩成本。帮助初创公司管理股权的平台Carta的彼得·沃克（Peter Walker）说，过去，创始人们喜欢吹嘘自己公司有多少员工，“而现在，‘看我的人多精简’反而成了一种荣誉勋章。”根据Carta的数据，初创公司从注册成立到雇佣第一名员工的平均时长，已从2022年的不足6个月，延长到了2024年的超过9个月。AI编程初创公司Base44最近被网站开发平台Wix以8000万美元的价格收购，而它仅仅只有8名员工。
当然，一切才刚刚开始。一方面，AI代理远非万无一失。今年6月，人工智能实验室Anthropic公布了一项实验结果，他们让其Claude Sonnet模型去运营公司总部的一台自动售货机。机器人的目标是避免亏损。它很擅长识别供应商、适应用户需求（甚至为了一名员工恶作剧般的要求，去寻找一块钨立方），但它却忽略了高利润的机会，出现了“幻觉”，提供了过多的折扣，最终没能赚到钱。
另一方面，其他因素也可能阻碍AI驱动下的创业热潮。尽管过去几十年里，互联网、社交媒体、软件即服务（SaaS）和云计算发展迅猛，但在疫情之前，由于人口老龄化等原因，美国的新企业成立数量一直增长乏力。这一人口结构带来的压力只会越来越大。
尽管生成式AI前景光明，但它也给创业者带来了新的难题。萨里大学的安娜贝尔·加维尔（Annabelle Gawer）指出，这项技术虽然降低了新业务的准入门槛，却也让复制创意变得轻而易举。除非创始人在自己的领域拥有独一无二的专业知识，否则可能很难维持竞争优势。
更重要的是，AI工具的供应，被科技巨头及其投资的实验室牢牢掌控着，例如微软支持的OpenAI，以及亚马逊和谷歌投资的Anthropic。加维尔女士将其与2010年代云计算的崛起相类比，当时的市场同样由这三家科技巨头主导。尽管云基础设施让初创公司的日子好过了许多，但也让它们对这个“三巨头联盟”产生了依赖，后者也因此攫取了这些初创公司所创造价值的相当一部分。去年，这三家巨头的净利润相当于美国企业总利润的7%，而十年前这个数字仅为2%。另一种可能是，科技巨头们会直接“借鉴”小公司的绝佳创意。 不过眼下，Solace公司的莎拉·吉廉对此倒是颇为乐观。她所说的“先发劣势”或许会“有点扫兴”，但也恰恰能验证她想法的价值。“也许他们（巨头）会找上门来说，‘我们想要Solace’。那我就会回答，‘太好了，卖给你！’” 看，这不就是一个典型的创业者心态么。