Auto Industry Faces Steep AI Learning Curve
A new study by Wards Intelligence finds some OEMs further ahead in raising their AI expertise than others and shows each taking slightly nuanced approaches to securing AI talent.
Traditional automakers and suppliers face a steep, expensive learning curve to applying artificial intelligence to autonomous vehicles, according to a new report from Wards Intelligence.
The report additionally finds some OEMs further ahead in raising their AI expertise than others, mostly on account of the aggressiveness of their AV plans, and shows each taking slightly nuanced approaches to securing AI talent.
“AI in Automotive” profiles 16 global automakers, digging into their AI strengths, as well as a host of old-line suppliers and newcomer disruptors to the space. It concludes the auto industry must quickly up its AI game and break from an historically rigid, common approach to designing, manufacturing and marketing its vehicles to capitalize on the promise of an AI-driven business.
Other findings of the study:
AI-piloted autonomous cars will require faster networks than available today and their data demands and data creation will result a storage crunch.
AI creates unique ethical dilemmas the industry must confront and align with varying societal norms.
AI is not just for the car. Automakers want to use it to make assembly-line robots smarter, sales forecasts more accurate and the buying process more enjoyable.
AI can be scary and its history is uneven, two factors that could affect its acceptance among consumers and regulators.
Included in “AI in Automotive” are Q&A’s with key industry executives and experts in the field of AI, results of an exclusive Wards Intelligence survey and feedback from survey takers on their perspective of AI.
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