Scaling Artificial Intelligence in Automotive Industry
Although AI offers vast implications for engineering, production, supply chain, customer experience, and mobility services, progress in AI-driven transformation has been sluggish and uneven due to lingering roadblocks. The number of automotive companies deploying AI at scale has grown from 7% in 2017 to 10% today, with OEMs generally making better progress than suppliers or dealers. Geographically, the US, where 25% of companies implement AI at scale, is leading the way in terms of progress, followed by the UK (14%) and Germany (12%). In terms of pronounced growth, China is making huge strides, having nearly doubled its share of scaled AI implementations, from 5% to 9%.
The new report by the Capgemini Research Institute, Accelerating automotive’s AI transformation: how driving AI enterprise-wide can turbo-charge organizational value, surveyed 500 executives from large automotive organizations in eight countries and interviewed a number of industry experts and entrepreneurs to understand how progress in deploying AI at scale can be accelerated. It also identifies 13 out of 45 high-benefit, low-complexity use cases organizations should focus on.
The research considers the following areas:
- Where the industry stands in scaling its AI implementations
- What concrete benefits can result from scaled initiatives
- Where automotive manufacturers should focus their AI investments
- Success factors and recommendations for scaling AI.
AI holds the key to the future of the automotive industry, but to reap its many benefits, organizations should accelerate AI adoption. In so doing, they should invest in high-value use cases that are easy to scale, promote effective governance, and proactively upskill their talent pools.