代理(哲学)
收入
创业
小企业
营销
商业计划书
经济
捐赠
领域(数学)
基线(sea)
工作(物理)
商业模式
生成语法
刻度(仪器)
商业化
体验式学习
商业分析
商业智能
业务
管理
群众
建议(编程)
人工智能
商业评论
考试(生物学)
风险投资
自营职业
实验经济学
新企业
联盟
商机
稀缺
业务分析
商业信息学
企业管理
国际商用机器公司
商业案例
经济影响分析
作者
Nicholas G. Otis,Rowan Philip Clarke,Solène Delecourt,David Holtz,Rembrand Koning
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2026-07-10
标识
DOI:10.1287/mnsc.2024.06909
摘要
Scalable and low-cost artificial intelligence (AI) assistance has the potential to improve firm decision making and economic performance, particularly in emerging markets. However, running a business involves a wide range of open-ended problems, making it unclear whether and how recent advances in AI can help business owners around the world make better decisions. In a field experiment with Kenyan entrepreneurs, we evaluated the impact of AI advice on small business revenues and profits by randomizing access to a GPT-4-powered AI business assistant. Although we are unable to reject the null hypothesis of no average treatment effect on firm revenues and profits, we find that the effect for entrepreneurs who were low performing at baseline is over 0.20-standard-deviations lower than for initial high performers. Subsample analyses show that low performers did nearly 10% worse because of the AI assistant, whereas high performers may have benefited by over 15%. This differential impact does not appear to result from differences in the questions posed to the AI or the advice that it provided but rather, from the advice that entrepreneurs chose to implement. More broadly, these results show that generative AI is already capable of impacting real-world business performance—although in uneven and sometimes unexpected ways. This paper was accepted by Anita McGahan, business strategy. Funding: This work was supported by the Weiss Fund, Harvard Business School, Berkeley Haas, the Cora Jane Flood Endowment at Berkeley Haas, the Agency Fund, the South Park Common Social Impact Fellowship, and the Digital Data Design Institute at Harvard. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06909 .
科研通智能强力驱动
Strongly Powered by AbleSci AI