Beyond being a mere technological trend, artificial intelligence (AI) is fundamentally transforming the safety, efficiency, and overall user experience of automobiles, and the automotive industry is rapidly being reshaped around AI.

At the Keysight World Tech Day webinar held online on the 27th, Thomas Goetzl, Executive Director of Automotive and Energy at Keysight Technologies, gave a presentation on the theme of "A New Era of the Automotive Industry Led by AI," outlining the direction of automotive innovation encompassing electric vehicles (EVs) and software-defined vehicles (SDVs).

General Manager Goetzl explained that AI is simultaneously boosting the efficiency and convenience of vehicles.

While conventional navigation systems were limited to displaying current traffic conditions, AI predicts future traffic flow by integrating factors such as day of the week, time of day, weather, and construction information.

This allows drivers to select more efficient routes, and vehicles can drive in conjunction with the signal system to reduce unnecessary congestion.

Voice-based interfaces are also becoming more natural due to the advancement of AI, changing the very way we interact with vehicles.

The role of AI in the electric vehicle sector is becoming even more prominent..

Applying AI to a Battery Management System (BMS) can extend battery life and determine the optimal charging time by analyzing charge/discharge patterns and sensor data.

Furthermore, AI serves as a core technology in the concept of 'Vehicle-to-Grid (V2G),' which utilizes vehicles as energy assets rather than merely a means of transportation.

This is because AI's prediction and decision-making capabilities are essential in the process of charging during periods of low power demand and utilizing vehicle batteries to stabilize the power grid when necessary.

Software-defined vehicles (SDVs) and autonomous driving technology also cannot be discussed without AI.

Generative AI increases development efficiency by supporting code writing and test automation in the software development process.

At the same time, AI models that have learned complex traffic environments understand road rules and driving cultures that differ by region, enabling more sophisticated judgments. This AI utilizes high-performance computing resources within the vehicle in parallel with cloud infrastructure to perform real-time decision-making and large-scale data analysis simultaneously.

AI is also establishing itself as a key tool for cost reduction and quality improvement in manufacturing sites.

It analyzes sensor data attached to production equipment to predict equipment failures in advance and detects defects early through image-based defect analysis.

This contributes to minimizing production interruptions and increasing efficiency throughout the supply chain.

On the other hand, General Manager Goetzl emphasized that as the use of AI expands, the challenge of 'trust' becomes even more important.

Unlike rule-based systems, AI results can vary depending on the training data and model structure.

Particularly in the automotive environment where safety is paramount, the bias of training data and model validation methods emerge as key issues.

For example, if the training data is structured around automobiles, judgments regarding pedestrians or motorcycles may become inaccurate.

Accordingly, countries are taking steps to establish regulations and standards to verify the quality and safety of AI.

"AI is no longer an option but a foundational technology that permeates the entire automotive industry," said General Manager Goetzl. "Only when explainability and verifiability are secured can AI establish itself as a safe decision-making tool."