Rand兰德：2024人工智能项目失败的根本原因以及如何成功-避免人工智能的反模式报告

to investigate why artificial intelligence and machine learning (AI/ML) projects fail, the authors interviewed 65 data scientists and engineers with at least five years of experience in building AI/ML models in industry or academia. The authors identified five leading root causes for the failure of AI projects and synthesized the experts' experiences to develop recommendations to make AI projects more likely to succeed in industry settings and in academia.By some estimates, more than 80 p