•    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.