The Driving Forces Behind the AI-Empowered Automotive Revolution

As automobiles begin to perceive the world and make decisions like humans, an AI-driven transportation revolution is quietly taking place.

AI is reshaping every aspect of human society. It is not only transforming knowledge systems, modes of thinking, and social division of labor, but also extending into the realms of morality and ethics. For the automotive industry, AI is not merely a technological tool but the core infrastructure of the future transportation ecosystem. As technology advances, automobiles are gradually evolving from purely mechanical products into integrated “mechanical + electronic + information” systems.  They are destined to become “intelligent mobile spaces.”

As Frank Zhao, honorary lifetime president of the International Federation of Automotive Engineering Societies, remarked, it is necessary, urgent, comprehensive, and scientifically possible for automakers to go all in on AI. Today, the intelligent transformation of automobiles is no longer a matter of choice but a requirement for survival. For automotive manufacturers, committing fully to AI is not simply following a trend, but the inevitable outcome of industry transformation.

The Evolution of Automobiles from “Functional Machines” to “Intelligent Entities”

Currently, automobiles are transitioning from SDVs (software-defined vehicles) toward AIDVs (AI-defined vehicles). Intelligent vehicles will evolve from possessing singular intelligent functions to becoming wholly integrated intelligent entities.
 

• The Evolution of the Smart Cockpit from Function Stacking to Cognitive Collaboration

While traditional smart cockpits have been centered on the idea of the “fridge, TV, and big sofa,” AI-native cockpits are redefining the relationship between humans and vehicles, shifting from passive response to proactive service. The key lies in multimodal perception and the deep application of large models. By using in-vehicle cameras, microphone arrays, and other sensors, the system can comprehensively assess a user’s emotions, fatigue levels, and even intentions, with understanding and decision-making performed by vehicle-end or cloud-based large models. If you were to enter a truly intelligent cockpit and say, “I feel a bit cold,” it would automatically raise the air-conditioning temperature, close the relevant window, and recommend a restaurant with hearty hot dishes to warm you up.

• Autonomous Driving: The “Dual-Brain Revolution” of Perception and Decision-Making

The two core pillars of autonomous driving technology are the “eyes” that perceive the world and the “brain” that makes decisions. At the perception layer, sensor fusion technology integrates data from LiDAR, millimeter-wave radar, cameras, and other sensors to create a precise 360-degree, blind-spot-free environmental model, effectively overcoming interference from adverse weather such as rain, snow, and fog. At the decision-making layer, a paradigm shift is underway from “rule-driven” to “end-to-end AI-driven” systems. The new generation of systems functions like an experienced driver. Rather than relying on programmers to predefine countless IF-THEN rules, it directly feeds sensor data into a massive neural network, instantly outputting control commands such as steering or braking. This ability of the system to handle complex scenarios makes it essentially “human.”

• V2X: Enabling Cars to “See” Beyond the Curve

V2X technology eliminates the physical limitations of standalone vehicle intelligence by connecting cars with everything, thus enabling a “god’s-eye view.” V2V (vehicle-to-vehicle) can instantly share information on sudden obstacles detected by the lead vehicle with the following vehicles, enabling beyond-line-of-sight early warnings. V2I (vehicle-to-infrastructure) uses smart roadside units to transmit the status of upcoming traffic lights, countdown times, and even recommended travel speeds to vehicles, enabling green-wave traffic flow that improves efficiency while also reducing energy consumption and emissions. By aggregating real-time data from vehicles across the entire road network, the cloud platform leverages AI algorithms to accurately predict short-term changes in future traffic flow. This provides support for dynamic traffic signal timing adjustments and the issuance of detour plans, optimizing traffic flow across vast areas.

• Vehicle Safety and Maintenance: From Passive Protection to Proactive Warning

AI can upgrade vehicle safety from “passive protection” at the moment of an accident to proactive warning and intervention before an accident occurs. Active safety, based on perception algorithms, enables vehicles to identify potential collision risks in advance, such as a pedestrian suddenly dashing onto the road, and consequently issue warnings or perform automatic emergency braking (AEB) to prevent accidents. An in-depth defense system built on vehicle networking and information security technologies can prevent remote attacks and malicious control. By continuously analyzing operational data from key components such as the engine and battery, the system can predict potential failures in advance and remind users to carry out maintenance, thereby enhancing driving safety and reliability.
 

Embracing AI and Welcoming Intelligent Companions

Far more than machines of steel, cars are evolving into intelligent companions with silicon brains. Through multi-sensor fusion and AI algorithms, vehicles are learning to perceive the world and make decisions. They are on their way to mastering the fundamentals of human driving. The transportation systems of the future will be a synergy of “smart cars” and “intelligent roads,” achieving deep collaboration among people, vehicles, and the environment.

The 3rd Avnet Automotive Ecosystem Summit (AAES2025) focused on three major technology topics: “Intelligent Driving,” “New Energy Power,” and “Car.AI.Cross-Border Collaboration,” with in-depth sharing on cutting-edge technologies and emerging trends. Avnet and its partners showcased more than 30 advanced solutions, including BMS, high-performance cockpits, driver assistance, smart gateways, perception and interaction, domain controllers, intelligent lighting, full-vehicle motor control and drive solutions, smart keys, and access control. It effectively laid out modular and scalable technology pathways for the design of next-generation intelligent vehicles.

Grace Dong, president of Avnet China, pointed out that in the next three to five years, AI will completely reshape the automotive ecosystem, ushering in new experiences and business models. She emphasized that the industry must address ongoing challenges such as data processing, hardware–software collaboration, balancing computing power and energy consumption, and regulatory compliance. In particular, at the supply chain level, the surging demand for high-performance chips, sensors, and edge computing platforms is testing the stability of the industry. By providing long-term, stable, and continuous design and supply chain services, Avnet continues to help its customers not only navigate but lead the AI-driven mobility revolution.