Reasons of an AI model not being efficient:
a. Lack of Training Data: If the data is not sufficient for developing an AI Model, or if the data is missed while training the model, it will not be efficient.
b. Unauthenticated Data / Wrong Data: If the data is not authenticated and correct, then the model will not give good results.
c. Inefficient coding / Wrong Algorithms: If the written algorithms are not correct and relevant, Model will not give desired output. Not Tested: If the model is not tested properly, then it will not be efficient.
d. Not Easy: If it is not easy to be implemented in production or scalable.
e. Less Accuracy: A model is not efficient if it gives less accuracy scores in production or test data or if it is not able to generalize well on unseen data. (Any three of the above can be selected)