Why solo founders became a red flag
For decades, investors have treated solo founders with suspicion. Venture capital firms, angels and accelerators all learned the same rule: great startups are built by teams. In Wasserman's (2012) dataset of high-potential startups, only 16.1% were solo-founded.
The reasons behind the red flag are familiar:
- Missing skills. One person rarely masters tech, product, sales and finance at the same time.
- Too much work. Building a company is more than one pair of hands can handle.
- Key-person risk. If the founder burns out, gets sick or leaves, the company stops.
- No one to challenge you. Without a partner, bad decisions go unquestioned.
- The signal. "If you couldn't convince anyone to join you, how will you convince customers and investors?"
These concerns made sense. But they all rest on one assumption: that the only way to cover these gaps is with another founder.
Teams were never risk-free
The irony is that founding teams were never a safe bet either.
Wasserman (2012) reports a survey in which venture capitalists attributed 65% of the failures in their portfolio companies to problems within the management team (Gorman & Sahlman, 1989, as cited in Wasserman, 2012). The people who were supposed to reduce the risk were often the risk itself.
This is not new. Long before startups were called startups, Stinchcombe (1965, as cited in Wasserman, 2012) argued that most of what makes young firms fragile lies inside the founding team: people need to build working relationships, find their roles and split the rewards among themselves. Each of these is a potential source of conflict.
And the conflicts are not about skills. They are about vision, strategy, control, equity and ego. Wasserman (2012) frames one of the core tensions as the choice between being "rich" or being "king": building value requires bringing in people who will, sooner or later, demand some control.
What Gen AI changed
Then, in November 2022, ChatGPT was released. And the assumption that only a co-founder could cover the gaps started to crack.
Cai et al. (2025) analysed more than 12 million new firm registrations and found a sharp surge in new firm creation after the release of ChatGPT, concentrated where AI skills were stronger. The new firms were leaner: less capital, fewer shareholders and smaller founding teams. The effect was strongest among first-time founders, exactly the people who traditionally lacked managerial and operational know-how.
A field experiment points in the same direction. Dell'Acqua et al. (2025) studied 776 professionals at Procter & Gamble and found that individuals with AI matched the performance of teams without AI. People using AI also produced more balanced solutions, regardless of their background: technical profiles came up with commercial ideas, and vice versa.
In other words, many of the gaps a co-founder used to fill, such as skills, workload and a second opinion, can now be partly covered by AI, and the rest by paid specialists, without giving away equity.
The imbalance
Put the two sides next to each other and something interesting appears.
Most of the reasons behind the solo-founder red flag are about capacity: skills, time, execution, a second opinion. These are exactly the areas where Gen AI is making the biggest difference.
The biggest risks inside founding teams, on the other hand, are human: disagreements about vision and strategy, fights over control and equity, partners who stop being aligned. Here AI hardly helps. No model will settle a dispute between two co-founders who no longer want the same company.
So in the post-Gen AI era, the risks of going solo are shrinking, while the risks of founding together stay right where they were.
But don't teams still win?
To be fair, there is evidence pointing the other way. Kim and Kang (2026) analysed more than 160,000 product launches on Product Hunt after the release of ChatGPT. They found a sharp increase in launches by solo entrepreneurs, but team-based ventures still dominated the top of the rankings.
This is important data, and it deserves attention. However, it measures products, not companies.
A successful company can have several products that failed along the way. And a successful product does not guarantee a successful company. A top ranking on launch day tells us about early popularity, not about revenue, survival, funding or exit. Besides, a sample of launches inevitably mixes side projects and weekend experiments with ambitious solo founders building a real company.
So it is a valuable signal, but it doesn't change the judgement. The question is still open at the level that matters most to investors: the company.
Will the balance tip?
For decades, the logic was simple: a team reduces risk, so a solo founder is a red flag.
Gen AI is changing one side of that equation. The capacity gaps that made solo founders risky can now be largely covered. The human risks that come with co-founders have not changed at all.
So here is my question to investors, venture capital firms, angels and accelerators: when you look at a solo founder today, are you still seeing the risk of 2015? Or has your view changed?
If you want to go further, read the briefing on evaluating solo founders.
References
- Cai, J. J., Gu, X., Sheng, L., Xia, M., Zhao, L., & Zhu, W. (2025). AI as "co-founder": GenAI for entrepreneurship (arXiv:2512.06506). arXiv. Preprint, not yet peer reviewed. https://doi.org/10.48550/arXiv.2512.06506
- Dell'Acqua, F., Ayoubi, C., Lifshitz-Assaf, H., Sadun, R., Mollick, E. R., Mollick, L., Han, Y., Goldman, J., Nair, H., Taub, S., & Lakhani, K. R. (2025). The cybernetic teammate: A field experiment on generative AI reshaping teamwork and expertise [Working paper].
- Kim, H., & Kang, H. (2026). Generative AI expands solo entrepreneurial entry, yet team advantage persists (extended abstract). Proceedings of the AAAI Symposium Series, 9(1), 215–216. https://doi.org/10.1609/aaaiss.v9i1.42928
- Wasserman, N. (2012). The founder's dilemmas: Anticipating and avoiding the pitfalls that can sink a startup. Princeton University Press.