If the graph teaches you anything, it’s that a tremendous quantity of data is required for the success of an ML project.
Organizations prefer to incorporate models meant to stimulate innovation on the guidance of data scientists without considering their alignment with their current non-digital culture.
The sector is suffering from a severe scarcity of data scientists. Although there are many engineers who complete courses and label themselves as data scientists.
ML projects tend to become outdated over time and struggle to remain the best solution to the business issue.
Leaders may lack the commitment and technical confidence required to complete a project. While they support the initiative because of its fame.