Some of the reasons causing the failure of AI projects-
Low data quality- Companies should verify that they have sufficient and relevant data from trusted sources representing their business activities, have correct labels, and are acceptable for the AI tool employed before commencing on an AI project.
Poor team collaboration- Data scientists, data engineers, IT professionals, designers, and line of business workers must work together to create a successful AI project.
Shortage of talent- Companies cannot achieve much with AI unless they have a team with sufficient training and business domain experience.