Generative AI Fuels Solo Entrepreneurship, but Teams Still Lead at the Top

• URL: http://arxiv.org/abs/2605.10291v1
• Date: Mon, 11 May 2026 09:53:44 GMT
• Title: Generative AI Fuels Solo Entrepreneurship, but Teams Still Lead at the Top
• Abstract summary: We find entrepreneurial entry increased sharply following the public release of ChatGPT-3.5.<n>This shift toward solo entry is particularly pronounced in categories that historically favored team-based ventures.<n>Team-based ventures are increasingly dominant in the top tiers of platform rankings.
• Score: 3.500192279092717
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recent advances in generative artificial intelligence (AI) are reshaping who enters entrepreneurship, but not who reaches the top of the quality distribution. Using data on over 160,000 product launches on Product Hunt, we find that entrepreneurial entry increased sharply following the public release of ChatGPT-3.5, driven disproportionately by solo entrepreneurs. This shift toward solo entry is particularly pronounced in categories that historically favored team-based ventures. However, much of this growth reflects low-commitment, experimental entry and does not translate into greater representation among the highest-quality outcomes. Team-based ventures are increasingly dominant in the top tiers of platform rankings. These findings suggest that generative AI lowers barriers to solo entrepreneurship while reinforcing team-based advantages.

Related papers

• Atria Dawn: The Dawn of Agentic Superintelligence [237.73474618289063]
  We introduce Atria Dawn Preview, a foundation agentic language model designed for scientific research and engineering.<n>We examine the real research-and-development process behind this model as a case study of human--AI collaboration.
  arXiv  Detail & Related papers  (2026-09-14T16:22:30Z)
• AI Premium [2.648339941888297]
  We build a high-frequency AI factor and decompose it into salient components.<n>We show that firms whose returns covary more positively with the AI factor -- high AI beta firms -- earn higher subsequent returns.<n>We provide early evidence of the rise of the agentic economy.
  arXiv  Detail & Related papers  (2026-06-29T17:28:22Z)
• Agents' Last Exam [275.79071391137074]
  Agents' Last Exam (ALE) is a benchmark designed to evaluate AI agents on long horizon, economically valuable, real world tasks with verifiable outcomes.<n>Developed in collaboration with 250+ industry experts, ALE covers non-physical industries defined with reference to O*NET / SOC 2018.<n>Current results show that the hardest tier remains far from saturated: across mainstream harness and backbone configurations, the average full pass rate is below 1%.
  arXiv  Detail & Related papers  (2026-06-03T20:20:46Z)
• Generative AI and the Productivity Divide: Human-AI Complementarities in Education [2.2940141855172036]
  Generative Artificial Intelligence (GenAI) is transforming how firms create, process, and apply knowledge.<n>On average, GenAI access significantly increased task performance, but the distribution of gains was highly uneven.<n>High-AIC participants realized outsized gains; low-AIC participants saw limited or even negative marginal returns.
  arXiv  Detail & Related papers  (2026-05-18T09:50:05Z)
• The Strategic Foresight of LLMs: Evidence from a Fully Prospective Venture Tournament [0.19116784879310025]
  We benchmarked forecasts against 346 experienced managers recruited via Prolific and three MBA-trained investors working under monitored conditions.<n>The results are striking: human evaluators achieved rank correlations with actual outcomes between 0.04 and 0.45, while several frontier LLMs exceeded 0.60, with the best (Gemini 2.5 Pro) reaching 0.74.<n>Neither wisdom-of-the-crowd ensembles nor human-AI hybrid teams outperformed the best standalone model.
  arXiv  Detail & Related papers  (2026-02-02T05:52:16Z)
• AI as "Co-founder": GenAI for Entrepreneurship [0.2858784880963941]
  This paper studies whether, how, and for whom generative artificial intelligence (GenAI) facilitates firm creation.<n>GenAI serves as a procompetitive force disproportionately boosting small-firm entry.
  arXiv  Detail & Related papers  (2025-12-06T17:36:36Z)
• How Founder Expertise Shapes the Impact of Generative Artificial Intelligence on Digital Ventures [0.28647133890966986]
  We find that the number of new venture launches increased and the median time to launch decreased significantly more in categories with relatively high GenAI usage.<n>GenAI's effect on new launches is larger for founders without managerial experience or education, while its effect on venture capital (VC) funding likelihood is stronger for founders with technical experience or education.
  arXiv  Detail & Related papers  (2025-11-09T21:16:02Z)
• LIMI: Less is More for Agency [49.63355240818081]
  LIMI (Less Is More for Intelligent Agency) demonstrates that agency follows radically different development principles.<n>We show that sophisticated agentic intelligence can emerge from minimal but strategically curated demonstrations of autonomous behavior.<n>Our findings establish the Agency Efficiency Principle: machine autonomy emerges not from data abundance but from strategic curation of high-quality agentic demonstrations.
  arXiv  Detail & Related papers  (2025-09-22T10:59:32Z)
• SEAgent: Self-Evolving Computer Use Agent with Autonomous Learning from Experience [71.82719117238307]
  We propose SEAgent, an agentic self-evolving framework enabling computer-use agents to evolve through interactions with unfamiliar software.<n>We validate the effectiveness of SEAgent across five novel software environments within OS-World.<n>Our approach achieves a significant improvement of 23.2% in success rate, from 11.3% to 34.5%, over a competitive open-source CUA.
  arXiv  Detail & Related papers  (2025-08-06T17:58:46Z)
• SciMaster: Towards General-Purpose Scientific AI Agents, Part I. X-Master as Foundation: Can We Lead on Humanity's Last Exam? [51.112225746095746]
  We introduce X-Master, a tool-augmented reasoning agent designed to emulate human researchers.<n>X-Masters sets a new state-of-the-art record on Humanity's Last Exam with a score of 32.1%.
  arXiv  Detail & Related papers  (2025-07-07T17:50:52Z)
• Generative AI Enhances Team Performance and Reduces Need for Traditional Teams [1.5031024722977635]
  We show that teams augmented with generative AI significantly outperformed those relying solely on human collaboration. Our analysis suggests that centralized AI usage by a few team members is more effective than distributed engagement.
  arXiv  Detail & Related papers  (2024-05-28T07:47:03Z)
• Using Deep Learning to Find the Next Unicorn: A Practical Synthesis [42.70427723009158]
  Venture Capital (VC) strives to identify and invest in unicorn startups during their early stages, hoping to gain a high return. Over the past two decades, the industry has gone through a paradigm shift moving from conventional statistical approaches towards becoming machine-learning based. In this work, we carry out a literature review and synthesis on DL-based approaches, covering the entire DL life cycle.
  arXiv  Detail & Related papers  (2022-10-18T13:11:16Z)
• Competing Bandits: The Perils of Exploration Under Competition [99.68537519404727]
  We study the interplay between exploration and competition on online platforms. We find that stark competition induces firms to commit to a "greedy" bandit algorithm that leads to low welfare. We investigate two channels for weakening the competition: relaxing the rationality of users and giving one firm a first-mover advantage.
  arXiv  Detail & Related papers  (2020-07-20T14:19:08Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.