The race to build fully autonomous cars has gone into hyper-drive, with major car-makers such as GM, Daimler, BMW and Audi promising SAE Level 5 autonomous driving by sometime in 2021. Goldman Sachs predicts that robo taxis will grow the ride-hailing and sharing business from $5 billion in revenue today to $285 billion by 2030. Autonomous driving will re-define mobility, and historic earning streams are sure to be toppled. Even with all the road testing the car-makers are doing, the only way the car companies can meet their ambitious goals is by leveraging the power of analytics and artificial intelligence (AI) to learn on real-world roads and accelerate development using simulations. The auto-makers are using simulation techniques such as hardware-in-the-loop (HIL) and software-in-the-loop (SIL) to make this happen.

Artificial intelligence (AI) has arrived in the mainstream and is augmenting decision making in many industries. From data-driven understanding of students' needs in education, to surrogate operators in combat and training in aviation, to robo advice dispensed in financial services, AI is available in multiple flavours to all takers. While the boardroom discusses how best to implement it, chief data officers seem poised to take centre stage when it comes to the rollout of AI. The emergence of the data chief reflects the starring role of data within commercially savvy organisations. A chief data officer (CDO) newcomer, Caroline Bellamy at mapping company Ordnance Survey, explains the mission: "Customers demand we do things [with their data] correctly and ethically. A lot of it is common sense, such as respecting individuals and rights, doing what we say we do. As data professionals, we have to hold in our hearts that we are doing the right things for both individuals and the organisation."