Thanks to cloud computing and distributed digital infrastructure, the one-person microenterprise It’s far from a novel concept. Cheap on-demand computing, remote collaboration, payment processing APIs, social media, and e-commerce marketplaces have made it easier to “go it alone” as an entrepreneur.
But what about scaling that one-person business into something meatier: a company of unicorn proportions?
Historically, this would have been an unfathomably difficult task, given the skills and resources required not only to scale a product but also to grow and maintain a sufficiently abundant customer base. But AI agents could crack the world’s would-be solopreneurs.
AI agents are all about embedding human workflows into software, freeing up the human to do more in less time. Agents can be assigned tasks and can make decisions with varying degrees of autonomy. Multiple AI agents could even collaborate on complementary tasks, paving the way for fully autonomous real work.
In a interview Last year with Reddit co-founder Alexis Ohanian, OpenAi's Sam Altman predicted this exact scenario.
“In my little group chat with my tech CEO friends, there’s a betting group that predicts that within this first year there will be a one-person billion-dollar company,” Altman said. “Which would have been unimaginable without AI, and now it can happen.”
At a discussion at the World Economic Forum's annual meeting in Davos last week, a panel of entrepreneurs and investors also discussed the prospect of a one-person billion-dollar company and, more importantly, what this could mean for the future of employment.
In humans we trust
Recent history reveals a number of billion-dollar companies. Microsoft dished out $2.5 billion to Minecraft maker Mojang, which had 40 employees. Facebook acquired WhatsApp for $19 billion when the messaging app maker had 55 employees. Two years before that, Facebook bought Instagram for $1 billion with just 13 employees in their ranks.
This shows that Internet technology has already spawned large companies with minimal staff. But this is not the same as a one-person unicorn.
kanja Qiu CEO of AI Research Lab Imbued which is building agents capable of reasoning and coding, recognizes that the kind of one-person companies AI is likely to help build in a big way are ones in which the product is largely self-sufficient.
When it comes to generating sales, it's not always the best product that wins. It's the people behind the product who have done a better job of building trust with customers. So if you need to proactively sell your product, you may need this type of staff.
"I think that human-to-human trust is very necessary and very important," Qiu added.
Benjamine Liu The CEO of AI drug development company Formation Bio is optimistic about the growing role AI is playing in his company.
“I think we’re living in one of the most exciting areas to be a construction company,” Liu said at Davos. “We have PhD-level intelligence at our fingertips, and we’re starting to see AI systems do the work of entire teams. I think in that world, AI-native companies have a pretty significant advantage.”
However, Liu echoed Qiu's sentiments: While one person's mega-business potential is real, it's actually meaningless from a business perspective, and it all comes down to the human condition that values relationships.
“The potential to get there is sooner than people think,” Liu said. “My view is that it will take a long time, because being an entrepreneur is a lonely journey, and you want a co-founder. Companies are still started by humans. I think you’ll want more people to share your journey.”
So the reality is that we could end up in a place where companies have always started: a founding team with complementary skills. But instead of scaling through incremental hiring, they maintain that initial leanness with AI agents that create the gap.
But even if the fabled one-person unicorn never happens, there's little doubt that the approaching AI agent train will disrupt the workforce in a big way.
The era of AI employees
While all of this still seems hypothetical, there is a deeper question to be asked. AI Agents are already affecting the workforce in the form of lawyers like Harvey or software engineers like Devin of Cognition.
AI Sales Agents are also booming with important VC supports. Companies like Artisan boasting that he wants to replace the human workforce – As demonstrated by their Dystopian commercial in San Francisco.
Many other companies are also laying the groundwork for AI Agents to flourish.
Lattice, a $3 billion HR and “people management” platform, goes further by giving “digital workers” official employee records which means that your clients' AI agents actually appear on the organizational chart, with a profile photo and a manager assigned to them.
Sarah Franklin who joined Lattice as CEO last year has called this transition a “great new era of collaboration,” where humans and AI agents work side by side. And what this means is managing these agents in a similar way to humans, to foster transparency and accountability.
“We want to prioritize the success of people, and when you’re working with AI agents, it’s important to understand what they’re tasked with doing,” Franklin explained at Davos. “It’s not saying that AI is human. It’s more the need to clearly identify where AI is. As AI speaks on behalf of brands and people, makes decisions on behalf of brands and people, and integrates with other systems, we need to be able to track it.”
Network organizational chart with Piper AI included.Image: Latex
But if businesses can operate at scale without a significant human workforce, what does this mean for society? People need to make money. They need a purpose.
As with previous industrial revolutions, a common ground around the AI revolution is that new jobs will emerge in the long term, we just don't know what they are yet.
"There will also be a lot of job creation." Mitchell Green founder of investment firm Lead Edge Capital, said in Davos. “If you think back to when the iPhone came out in 2007, Uber and Airbnb are now $100 billion companies. They couldn’t have existed before this. Where opportunities may exist for companies, we’re not even thinking about them yet, they’re going to be the next big businesses.”
However, that doesn't mean there won't be big ones. moments of pain or near-term uncertainty. And as we are already seeing with Chinese AI sensation DeepSeek, the rate of AI advancement is significant in terms of the cost/performance ratio of AI models. And this could be a key differentiator versus previous industrial and technological revolutions: we may not be able to adapt fast enough.
“I think there’s a lot of talk in terms of retraining and upskilling,” Liu said. “But there’s something quite unique about the pace of developments and how quickly these models are improving, specifically where we’re seeing these AI systems doing the work of entire teams.”
AIS Manager
There is a general consensus, regardless of the rate of change, that we will all have to learn not only to live with AI, but also learn how to use it to thrive in the workplace.
With you.com, for example, companies can access its API to bring real-time web search to any large language model (LLM). While it offers its own set of agents for specific tasks, companies you can also create their custom agents and choose their preferred AI model and give it instructions based on the data sources they need to connect to.
“We, as CEOs, will be the first generation to manage people and AI,” said You.com CEO Richard Socher in Davos. “But I think the most interesting change here is that every individual contributor, every employee, will become an AIS manager. And in that sense, everyone will become an entrepreneur.”
So it’s still too early to see a true one-person unicorn company. However, the principle behind the sentiment has already been tested, as we’ve seen with WhatsApp’s incredibly high value-to-sales ratio, which worked out to $345 million for each employee at the time Facebook bought it.
Even Nvidia, with a market cap of more than $3 trillion, has a relatively thin workforce of less than 30,000 employees – That’s the equivalent of about $100 million in value per employee.
With the right kind of company and the right execution, it’s hard to see how AI won’t push these dollar figures up as employee numbers go down. But in all likelihood, it will come down to whether there’s the desire for one person to build themselves up, with enough business knowledge to embed a strong, defensible business model that another can’t easily replicate.
But whether society will be ready to handle this is a completely different question.
