Why AI Projects Fail: Lessons From New Product Development

Q1 Business, Management and Accounting

IEEE Engineering Management Review Pub Date : 2024-06-26 DOI:10.1109/EMR.2024.3419268

Robert G. Cooper

引用次数: 0

Abstract

The majority of artificial intelligence (AI) projects in business do not succeed. Despite numerous opinion pieces on the causes of these failures, there is a notable scarcity of solid research on the subject. Analysis of the available data shows that the reasons for AI failures are strikingly similar to those identified in the extensively studied field of new product development (NPD). Furthermore, effective strategies from NPD can be adapted to address AI project failures. This article identifies seven primary reasons for AI failures in business, primarily stemming from poor business practices, and offers corresponding recommendations for improvement.

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人工智能项目失败的原因：新产品开发的教训

大多数人工智能（AI）项目在商业上都没有成功。尽管关于这些失败的原因有许多观点，但关于这一主题的可靠研究却明显缺乏。对现有数据的分析表明，人工智能失败的原因与广泛研究的新产品开发（NPD）领域中发现的原因惊人地相似。此外，NPD的有效策略可以用于解决人工智能项目的失败。本文确定了人工智能在商业中失败的七个主要原因，主要源于糟糕的商业实践，并提供了相应的改进建议。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Engineering Management Review Business, Management and Accounting-Management of Technology and Innovation

CiteScore

7.40

自引率

0.00%

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