A/B testing and experimentation play crucial roles in model deployment. By evaluating the performance of different model versions, organisations can make informed decisions about deployment. A/B testing involves dividing users into groups and exposing them to various model versions. Subsequently, analysing outcomes helps identify the superior variant. This iterative approach facilitates continuous improvement and optimization of deployed models, ensuring they effectively achieve desired objectives.