Over the last decade, artificial intelligence (AI) and machine learning (ML) techniques have developed at an unprecedented pace, and it is now evident that many scientific disciplines can hugely benefit from these developments provided they explore more data centric methodologies. The science community is currently exploring how the new AI and machine learning techniques can be exploited to further enhance our Earth-system prediction capabilities and first results show exciting potential. However, the scope and speed of these AI/ML developments also generate challenges for weather and climate modelling centres such as ECMWF. These challenges regard the necessary knowledge that needs to be established, the software and hardware infrastructures that need to be developed and used, and the integration of machine learning and conventional tools across the entire prediction workflows, which are continuously evolving. It is fundamental that these challenges are addressed and that the weather and climate modelling community and ECMWF's Member and Co-operating States are enabled to make the best possible use of machine learning in the years to come.