•    Discussion challenges of deploying the technology.
•    Looking at safety, data sharing, and ethical concerns regarding AI and data.
•    Debating where AI works and where it doesn’t.
•    Exploring alternative solutions such as machine learning, optimisation, and simulation.
•    Unravelling the best way to use data and how it can add value.
•    Data interoperability: Production data vs Data points generated by OEMs – Best practices and how to move forward.