The evolution of car manufacturing has always been closely linked to technological advancements. From the early days of conveyor belts to the robotics revolution, each leap forward has reshaped the industry. Today, artificial intelligence (AI) is once again revolutionizing the process, extending its impact beyond the factory floor. AI-assisted cameras on production lines now detect defects with greater speed and accuracy, while smart cameras enhance employee safety. On the racetrack, machine-learning algorithms provide race teams with real-time data crucial for victory, and dealerships leverage AI to offer more personalized services to customers.

How is AI Enhancing Speed in Racing?

AI-powered tools offer a significant advantage in terms of speed, automating data analysis to enable faster decision-making. In racing, where speed is paramount, this is particularly beneficial. The Ducati Lenovo Team in MotoGP, for instance, uses AI to analyze data from their bikes, allowing them to make rapid adjustments between track sessions. Each Ducati bike, equipped with around 50 sensors, generates 100GB of data every race weekend. AI-optimized servers process this data, providing insights on everything from tire selection to optimal cornering trajectories. These insights not only enhance racing performance but also contribute to the safety and design of consumer bikes, such as the Ducati Panigale V4.

What Role Does AI Play in Manufacturing?

AI-powered analytics streamline key production-line tasks, outperforming human capabilities in speed and accuracy. Manual inspections are prone to errors, whereas automated checks run continuously, identifying defects at every stage and allowing workers to focus on core tasks. For example, Lotus Group’s electric vehicle production employs machine vision solutions with 99% accuracy, preventing bottlenecks in quality inspections. AI solutions like those from ByteLake inspect products and processes, using cameras to detect defects and improve operations. These systems also capture engine sounds to identify issues, a challenging task in noisy factory environments.

How is AI Improving Safety and Logistics?

AI cameras and computer vision are transforming safety protocols by identifying potential hazards before they occur. Solutions like Graymatics’ LabVista detect risks such as missing protective equipment or unauthorized access to restricted areas. In logistics, AI tracks inventory movement and monitors production lines to ensure efficient use of raw materials. Predictive maintenance, enabled by AI, allows business leaders to plan ahead, reducing the costs associated with unexpected production halts.

How is AI Being Utilized in Dealerships?

AI is also making its mark in dealerships, addressing challenges in maintenance and servicing. General Motors, for example, uses AI-powered scanners from UVeye in 300 dealerships to identify vehicle issues with over 90% accuracy. This technology reduces the need for manual checks, allowing service departments to focus on repairs, thus enhancing customer experience by minimizing wait times.

What Should Automotive Leaders Consider When Implementing AI?

For IT leaders in the automotive sector, selecting the right AI solutions is crucial. It’s essential to engage with teams to identify solutions that align with business goals like cost reduction and efficiency improvement. Business leaders must also ensure they have the necessary infrastructure to support AI solutions, as not all providers offer comprehensive solutions for every operational area.

The automotive industry’s growth has always been fueled by technological innovation, and AI represents the next significant leap. From factory efficiencies to insights from racing data, AI is poised to drive the industry forward, making production lines faster, safer, and more cost-effective.

About the author: Felix Marquez is AI Marketing Program Analyst at Lenovo