Common challenges in AI and ML implementation include acquiring quality data, ensuring data privacy and security, selecting suitable algorithms and models, interpreting complex model outputs, scaling models for large datasets, etc.

While there are no strict prerequisites, having a clear understanding of the problem to be solved, access to relevant and high-quality data, and a basic understanding of AI and ML concepts can be beneficial.