AI as "Co-founder": GenAI for Entrepreneurship
- URL: http://arxiv.org/abs/2512.06506v1
- Date: Sat, 06 Dec 2025 17:36:36 GMT
- Title: AI as "Co-founder": GenAI for Entrepreneurship
- Authors: Junhui Jeff Cai, Xian Gu, Liugang Sheng, Mengjia Xia, Linda Zhao, Wu Zhu,
- Abstract summary: 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.
- Score: 0.2858784880963941
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This paper studies whether, how, and for whom generative artificial intelligence (GenAI) facilitates firm creation. Our identification strategy exploits the November 2022 release of ChatGPT as a global shock that lowered start-up costs and leverages variations across geo-coded grids with differential pre-existing AI-specific human capital. Using high-resolution and universal data on Chinese firm registrations by the end of 2024, we find that grids with stronger AI-specific human capital experienced a sharp surge in new firm formation$\unicode{x2013}$driven entirely by small firms, contributing to 6.0% of overall national firm entry. Large-firm entry declines, consistent with a shift toward leaner ventures. New firms are smaller in capital, shareholder number, and founding team size, especially among small firms. The effects are strongest among firms with potential AI applications, weaker financing needs, and among first-time entrepreneurs. Overall, our results highlight that GenAI serves as a pro-competitive force by disproportionately boosting small-firm entry.
Related papers
- 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) - Leveraging Artificial Intelligence as a Strategic Growth Catalyst for Small and Medium-sized Enterprises [0.0]
Artificial Intelligence (AI) has transitioned from a futuristic concept reserved for large corporations to a present-day, accessible, and essential growth lever for Small and Medium-sized Enterprises (SMEs)<n>For entrepreneurs and business leaders, strategic AI adoption is no longer an option but an imperative for competitiveness, operational efficiency, and long-term survival.<n>The quantitative evidence supporting AI adoption is compelling; 91% of SMEs using AI report that it directly boosts their revenue.<n>Beyond top-line growth, AI drives profound operational efficiencies, with studies showing it can reduce operational costs by up to 30% and save businesses more than 20 hours of valuable
arXiv Detail & Related papers (2025-09-18T01:56:04Z) - Openness in AI and downstream governance: A global value chain approach [0.0]
Openness in AI highlights an emerging ecosystem of open AI models, datasets and toolchains.<n>It poses questions as to whether open resources can support technological transfer and the ability for catch-up, even in the face of AI industry power.<n>This work extends previous mapping of AI value chains to build a framework which links foundational AI with downstream value chains.
arXiv Detail & Related papers (2025-09-12T13:12:09Z) - AI is the Strategy: From Agentic AI to Autonomous Business Models onto Strategy in the Age of AI [0.0]
We argue that we are now entering a phase where agentic AI can execute the core mechanisms of value creation, delivery, and capture.<n>This shift reframes AI not as a tool to support strategy, but as the strategy itself.<n>We show how ABMs reshape competitive advantage through agentic execution, continuous adaptation, and the gradual offloading of human decision-making.
arXiv Detail & Related papers (2025-06-19T11:11:06Z) - From Model Design to Organizational Design: Complexity Redistribution and Trade-Offs in Generative AI [44.99833362998488]
We argue that viewing AI as a simple reduction in input costs overlooks two critical dynamics.<n>The GAS trade-off, therefore, does not disappear but is relocated from the user to the organization.<n>This study advances AI strategy by clarifying how scalable cognition relocates complexity.
arXiv Detail & Related papers (2025-06-10T15:22:09Z) - An AI Capability Threshold for Rent-Funded Universal Basic Income in an AI-Automated Economy [2.6451153531057985]
We derive the first closed-form condition under which AI capital profits could sustainably finance a universal basic income.<n>We analyze how the AI capability threshold--defined as the productivity level of AI relative to pre-AI automation--varies under different economic scenarios.
arXiv Detail & Related papers (2025-05-24T13:08:13Z) - From Defects to Demands: A Unified, Iterative, and Heuristically Guided LLM-Based Framework for Automated Software Repair and Requirement Realization [44.99833362998488]
This manuscript signals a new era in the integration of artificial intelligence with software engineering.<n>We present a formalized, iterative methodology proving that AI can fully replace human programmers in all aspects of code creation and refinement.
arXiv Detail & Related papers (2024-12-06T14:54:21Z) - Engineering Trustworthy AI: A Developer Guide for Empirical Risk Minimization [53.80919781981027]
Key requirements for trustworthy AI can be translated into design choices for the components of empirical risk minimization.
We hope to provide actionable guidance for building AI systems that meet emerging standards for trustworthiness of AI.
arXiv Detail & Related papers (2024-10-25T07:53:32Z) - Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI [67.58673784790375]
We argue that the 'bigger is better' AI paradigm is not only fragile scientifically, but comes with undesirable consequences.<n>First, it is not sustainable, as, despite efficiency improvements, its compute demands increase faster than model performance.<n>Second, it implies focusing on certain problems at the expense of others, leaving aside important applications, e.g. health, education, or the climate.
arXiv Detail & Related papers (2024-09-21T14:43:54Z) - 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) - Future Computer Systems and Networking Research in the Netherlands: A
Manifesto [137.47124933818066]
We draw attention to CompSys as a vital part of ICT.
Each of the Top Sectors of the Dutch Economy, each route in the National Research Agenda, and each of the UN Sustainable Development Goals pose challenges that cannot be addressed without CompSys advances.
arXiv Detail & Related papers (2022-05-26T11:02:29Z)
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.