"Assessment of the data showed the automotive industry has moved past the hype to tackle the complexities of real-world operationalisation. Overall, the research shows that the industry is moving out of the exploratory phase and into making more practical decisions about what actually works, and indeed what pays off."
"In particular, there has been a marked shift away from automakers selling drivers' data, and instead, the original equipment manufacturers (OEMs) are finding the data is more valuable invested back into development - such as ADAS, product improvement and diagnostics - to create value-generating opportunities. In short, OEMs are using their data as the building blocks of intelligent, continuously improving vehicles."
"Predictive maintenance was found to be both the top artificial intelligence (AI) use case and the top revenue driver - one of the first clear ROI stories in this space - and there were clear regional differences in trends. For example, while China is focusing on enhancing in-car experiences and personalisation, North America is more focused on cost reduction and service."
"Specifically, the research established that smart diagnostics and predictive maintenance are the "killer apps for AI". Smart diagnostics and predictive maintenance emerged as the top priorities for AI, cite"
Automotive software-defined vehicles generate operational value even as automakers reduce expectations of revenue from selling vehicle data. Research based on responses from 559 automotive professionals across major markets indicates the industry has moved beyond hype and is making practical decisions about what works and pays off. A shift away from selling drivers’ data is evident, with OEMs investing collected data back into development for ADAS, product improvement, and diagnostics. Predictive maintenance is identified as the top AI use case and the top revenue driver, with regional differences in priorities. China emphasizes in-car experiences and personalisation, while North America focuses on cost reduction and service. Smart diagnostics and predictive maintenance are described as the leading AI priorities.
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