Why Products Fail and How AI Can Intervene

Abstract

Product failures can lead to serious financial losses and damage a company’s reputation. This thesis explores the reasons behind these failures and how artificial intelligence (AI) can help identify and prevent issues before they escalate. Through case studies and industry analysis, the research pinpoints key factors that contribute to product failures, such as inadequate market research, poor design, and bad timing. It also shows how AI can effectively handle these challenges.
The findings of the study suggest that using predictive analytics early in market research and design can significantly improve a product's chances of success. This thesis offers advice for companies on integrating AI into their product development life cycle. This thesis highlights the importance of real-time data analysis, choosing the right models, and taking a systematic approach to implementation. By highlighting how AI can lower product failure rates and promote sustainable growth, this study adds valuable insights to both academic research and real-world business strategies.