MHP Study: AI Reshapes Global Auto Industry Trust Landscape
Like many global industries, the automotive industry is at a critical point in AI adoption, as manufacturers balance investment in AI technology against consumer acceptance of paying for these features.
As vehicle makers integrate AI across functions from autonomous driving to predictive maintenance, they are forced to compete with technology companies entering the automotive space.
The integration of AI in vehicles represents a shift in how cars operate and interact with drivers. Functions range from AI navigation systems that predict traffic patterns to maintenance alerts that anticipate mechanical issues before they occur.
As Tesla, NIO and traditional manufacturers compete to differentiate their vehicles through technology, MHP Consulting – a Porsche-owned global technology and management consultancy – has released research indicating a stark divide between consumer interest and willingness to pay for AI features in vehicles across global markets.
European drivers resist AI premium pricing in vehicles
The study, which surveyed 4,700 participants across China, the US, Germany, the UK, Italy, Sweden and Poland, reveals that while 79% of European respondents express interest in AI-supported vehicle functions, only 23% would accept additional charges for these features.
This resistance to AI-related costs emerges despite broad interest in specific applications such as driver assistance systems, which use algorithms to support vehicle control and safety features, intelligent route planning that adapts to real-time conditions, and predictive maintenance that anticipates vehicle service needs before failures occur.
Marcus Willand, Partner at MHP, says: “The figures show that the prospect of greater safety and comfort due to AI can motivate purchasing decisions. However, the European respondents in particular are often hesitant and price-sensitive.”
European risk assessment shows mixed response
In Europe, 39% of respondents consider AI opportunities and risks to be balanced, while 24% view risks as outweighing benefits. This cautious stance contrasts with broader industry developments, where AI integration spans vehicle development, manufacturing, and consumer applications.
The research suggests a correlation between understanding and acceptance. Only 60% of global respondents indicate they comprehend AI applications in vehicles, with European comprehension at 54%, indicating potential barriers to adoption.
Chinese market shows contrasting AI acceptance levels
The research identifies significant regional variations in AI perception. In China, 48% of respondents view in-car AI applications as an opportunity, compared to 23% in Europe. The understanding of AI implementation in vehicles also varies, with 80% of Chinese respondents claiming comprehension of these systems.
Chinese consumers demonstrate higher willingness to pay for AI features, with 39% accepting additional charges compared to 23% in Europe. This acceptance predominantly applies to features installed at point of purchase rather than post-sale activations or subscription models.
Dr. Nils Schaupensteiner, Associated Partner at MHP, says: “Automotive companies need to create innovations with clear added value and develop both direct and indirect monetisation of their AI offerings, for example through data-based business models and improved services.”
Manufacturing sector faces AI implementation challenges
The automotive sector demonstrates caution in AI investment compared to other industries, with hesitation in allocating computing capacity, team resources and budgets. The research indicates this stems from uncertainty about implementation strategies and return on investment calculations.
- 79% of European drivers express interest in AI-supported vehicle functions
- 80% of Chinese respondents understand AI systems in vehicles, compared to 54% in Europe
- 64% of consumers trust traditional car manufacturers with AI development versus 50% for tech firms
AI applications in manufacturing include pattern recognition systems that identify production anomalies through visual and acoustic data analysis. These systems support quality management in component production and assembly processes.
Data management systems powered by AI assist in harmonising vehicle information, while machine learning algorithms support pricing decisions in regional mobility markets. AI-based chatbots and voice recognition systems enhance customer service interactions.
Traditional manufacturers lead AI trust rankings
The research indicates that established vehicle manufacturers maintain a trust advantage over technology companies in AI implementation. Automotive brands receive 64% trust ratings for AI development, compared to 50% for technology firms including Apple, Google and Microsoft.
Vehicle purchasing intentions reflect this trust differential. AI functions would influence 84% of Chinese drivers' vehicle purchases, compared to 48% of European drivers. These figures suggest regional variations in the perceived value of AI technology in vehicles.
Automotive companies need to create innovations with clear added value and develop both direct and indirect monetisation of their AI offerings.
The study examines AI implementation across development, production, and vehicle applications, providing insights for automotive industry decision-makers navigating technological transformation.
Augustin Friedel, senior manager at MHP, says: “It is worth OEMs and suppliers considering the opportunities offered by the new technology along their entire value chain. However, the possible uses are diverse and implementation is quite complex.”
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