Accelerating Automotive’s AI Transformation

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.

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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.

 

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