Andy Cousins explores the potential of AI across a range of applications and the importance of enterprise resource planning to support it.
The global automotive industry, like every other industry on the planet, is gearing up for the opportunities created by artificial intelligence (AI). When combined with machine learning (ML), AI can detect defects and errors in parts and materials to increase factory efficiency. For example, Audi is using AI-enabled cameras to detect cracks in metal sheets that are invisible to the human eye. General Motors is using sensors to monitor the atmosphere in its factories to create optimal conditions for paint to harden.
AI and ML can also be used to maintain the integrity of the supply chain far beyond the factory floor. This doesn't just apply to car assembly: manufacturers can change production of certain models in response to real-time demand analysis. For example, Volkswagen uses economic, political, and even weather data to forecast car sales in 120 countries.
Individually, these AI and ML-powered solutions improve operational efficiencies across the industry, and together they provide actionable insights that improve operational performance, further assisting automakers, dealers and installers in their quest to gain a competitive edge.
But AI can only achieve these things with access to quality data that can be properly leveraged as part of an overall data-first business strategy. That's one reason why industry-specific enterprise resource planning (ERP) solutions are essential for emerging AI technologies. When companies invest in ERP, they not only lay the foundation for more agile, efficient, and resilient operations, they also pave the way for an AI-enabled future.
“Cognitive ERP” refers to a system that incorporates AI into this process, designed to rapidly analyze large amounts of data and transform it from a system of record into an orchestrated system of action.
Prepare for AI FOMO
The allure of AI in the automotive industry is undeniable, with visions of self-optimizing production lines and predictive maintenance models. However, amid all the noise, the industry must be wary of digital “FOMO” that could lead to a hasty adoption of AI without a strong data foundation. A data-centric approach anchored in a modern, cognitive ERP system is essential.
AI can only achieve this if it has access to quality data that can be properly leveraged as part of an overall data-first business strategy.
In the automotive industry, ERP does more than manage resources. It integrates myriad data streams, from supply chain logistics to customer behavior insights, into one coherent, actionable whole. This integration allows automakers to leverage cognitive ERP for more than just operational efficiency. It becomes a strategic asset in predicting market trends, customizing vehicle features, and optimizing the entire value chain. Automotive leaders must focus on developing a comprehensive understanding of their data landscape, identifying and bridging data silos, and ensuring robust and secure data practices are in place. This strategic alignment of ERP and AI initiatives ensures investments are future-proof and deeply aligned with the industry's unique demands, from the factory to the showroom.
A planned cognitive ERP strategy can help the automotive industry break new ground in automotive excellence and drive 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 position of Automotive World Ltd.
Andy Cousins is Executive Vice President and Head of International at Epicor Software.
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