Pilot Early, Commit Late: A Real-Options Model of Enterprise AI Adoption under Rapid Technological Progress· 快速技术进步下的企业 AI 采纳模型
Artificial intelligence presents firms with an unusual timing problem. The technology frontier is improving rapidly, implementation is partly irreversible, and organization-specific capabilities are accumulated through action. This paper develops a two-period decision model of AI deployment under uncertainty in which a firm chooses among immediate deployment, a limited pilot, and waiting. Deployment earns current operating value but exposes the firm to architectural obsolescence; waiting preserves the option to adopt after the frontier is observed; a pilot sacrifices current operating value to build organization-specific learning without full commitment. The model yields five central timing results and a sixth comparative result on where learning occurs. First, a mean-preserving increase i
企业 AI 采纳模型探讨快速技术进步下的决策策略。
- 核心方法
- 构建了两期决策模型，考虑了即时部署、有限试点和等待三种选择，分析了不同策略下的企业价值和风险。
- 适合谁读
- 研究者 / 产品 / 管理者
- 要解决的问题
- 论文探讨企业在快速技术进步背景下如何决策 AI 的部署时机，以平衡当前价值与未来技术过时风险。
- 关键实验
- 未提供
- 主要贡献
- 提出了在技术不确定性和快速进步条件下，企业 AI 采纳的最优时机策略，强调了试点学习的重要性。
- 意义与局限
- 为企业的 AI 采纳提供理论指导，有助于降低因技术过时带来的风险。局限在于模型假设了两期决策框架，可能不适用于所有企业情境。