Automotive manufacturers and suppliers are faced with increasing regulatory requirements and growing consumer mistrust. This creates a need for increased auditability, traceability of parts and operational transparency throughout the supply chain, which is driving the move towards AI machine vision. In cooperation with the market research institute Censuswide, Zebra therefore surveyed 500 decision-makers from the automotive and related supplier industry about their use of and experience with AI-supported image processing. The result: According to the current 'AI Machine Vision in the Automotive Industry Benchmark Report', 49% of OEMs, 40% of Tier 1 and 35% of Tier 2 suppliers in Germany use AI machine vision. This compares to 56% of OEMs, 63% of Tier 1 and 44% of Tier 2 suppliers in the UK.

More than 20% of all respondents in the UK and Germany stated that they would like to learn more about AI machine vision systems or have already started sourcing them. However, for those who are delaying the adoption of AI-powered machine vision, it could become more difficult to gain a competitive advantage. Especially as the automotive manufacturers and suppliers surveyed in Germany and the UK report increasing pressure on issues of sustainability, transparency and performance. "It is worrying that more than a third - 34% - of German and almost a quarter - 24% - of UK automotive executives say they are not using any form of AI, such as deep learning, in machine vision. Even more worrying is that they don't recognize the relevance," comments Stephan Pottel, Automotive Manufacturing Practice Lead EMEA, Zebra Technologies.

The data also shows that there is still room for growth in AI performance in industrial image processing. Of those surveyed who use AI in machine vision in Germany, almost one in five (18.73%) say that their AI could work better or do more.

The survey was conducted by Censuswide in May 2023. It surveyed 250 decision-makers from the German and British automotive industries who are responsible for image processing.