兰德公司：2024人工智能项目失败的五大根本原因及其成功之道-避免AI的反模式（英文版）（20页）.pdf

1、JAMES RYSEFF,BRANDON DE BRUHL,SYDNE J.NEWBERRYThe Root Causes of Failure for Artificial Intelligence Projects and How They Can SucceedAvoiding the Anti-Patterns of AIArtificial intelligence(AI)is widely recognized as technology with the potential to have a transformative effect on organizations.1 Al

2、though AI was once reserved for advanced tech-nology companies with the ability to hire top talent and spend millions of dollars,all types of organizations are adopting AI today.Private-sector investment in AI increased 18-fold from 2013 to 2022,2 and one survey found that 58 percent of midsize corp

3、orations3 had deployed at least one AI model to production.4 Similarly,the U.S.Department of Defense(DoD)is spending$1.8billion each year on military applications for AI,and DoD leaders have identified AI as one of the most crucial technologies to the future of warfare.5AI is already making impacts

4、across a wide variety of industries.Pharmaceutical companies are using it to accelerate the pace and success rate of drug development.6 Retailers,such as Walmart,are deploying AI for predictive analytics so that they know when to restock inventory and how to optimize their end-to-end supply chains.7

5、 Finally,in the defense realm,AI is piloting fighter jets,8 detecting enemy submarines,9 and improving commanders awareness of the battlefield.10 These examples dem-onstrate the relevance of AI to organizations in a variety of industries and for a variety of use cases.However,despite the promise and

6、 hype around AI,many organizations are struggling to deliver working AI applications.One survey found that only 14 percent of organizations responded that they were fully ready to adopt AI,even though 84 percent of business leaders reported that they believe that AI will have a significant impact on