Andy Coussins explores the potential for AI within various applications and the importance of Enterprise Resource Planning to support it
The global automotive industry—just like every other sector on the planet—is gearing up for the opportunities created by artificial intelligence (AI). When combined with machine learning (ML), AI has the power to make factories more efficient by spotting flaws and errors in components and materials. Audi, for instance, uses AI-enabled cameras to detect cracks in sheet metal that aren’t visible to the human eye. General Motors uses sensors to monitor factory atmospherics to create optimum conditions to let paint set and harden.
AI and ML can also be used to maintain supply chain integrity way beyond the factory floor. This doesn’t just apply to automotive assembly. Manufacturers can alter the production of certain models depending on real-time demand analytics. For example, Volkswagen uses economic, political and even weather data to predict car sales in 120 countries.
On their own, these AI and ML-powered solutions improve the operational efficiency of the industry. Together, they provide actionable insights that enhance operational performance giving automotive manufacturers, sellers and installers an extra gear as they look to sharpen their competitive edge.
But AI can only do these things if it has access to quality data that can be properly leveraged as part of a holistic data-first business strategy. That’s one of the reasons why industry-specific Enterprise Resource Planning (ERP) solutions are essential for emerging AI technologies. When businesses invest in ERP, not only are they laying the foundations for more agile, efficient, and resilient operations, they are also paving the way for an AI-enabled future.
‘Cognitive ERP’ refers to systems that are designed to incorporate AI into this process, quickly analysing large volumes of data and converting it from a system of record into an organised system of actions.
Guard against AI FOMO
The allure of AI in the automotive world is undeniable, with visions of self-optimising production lines and predictive maintenance models. However, amidst this buzz, the industry must guard against the digital ‘FOMO’ that can lead to hasty AI adoptions without a solid data foundation. It’s essential to proceed with a data-centric approach anchored in a modern Cognitive ERP system.
AI can only do these things if it has access to quality data that can be properly leveraged as part of a holistic data-first business strategy
In the automotive sector, ERP doesn’t just manage resources; it unifies the myriad data streams—from supply chain logistics to customer behaviour insights—into a coherent, actionable whole. This integration enables automotive manufacturers to leverage Cognitive ERP for more than just operational efficiency; it becomes a strategic asset in forecasting market trends, customising vehicle features, and optimising the entire value chain. For automotive leaders, the focus should be on developing a comprehensive understanding of their data landscape, identifying and bridging data silos, and ensuring robust, secure data practices are in place. This strategic alignment between ERP and AI initiatives will ensure that investments are both future-forward and deeply aligned with industry-specific demands, from shop floor to showroom.
With a measured Cognitive ERP strategy, the automotive industry can shift to pioneering new frontiers of automotive excellence, driving innovation, efficiency, and customer satisfaction in a data-driven era.
The opinions expressed here are those of the author and do not necessarily reflect the positions of Automotive World Ltd.
Andy Coussins is Executive Vice President and Head of International at Epicor Software
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