Cloud or legacy infrastructure is often used for early AI development or proof of concept, but when AI is used at production scale, data scientists need to consider infrastructure that is optimised for AI.
Considerations should include:
Data set size and growth
Cost and availability of high performance GPUs, storage, and networking
Security, control, governance, and data ownership requirements.
Often, a hybrid or on-prem solution will offer better and faster results  with lower total cost of ownership.