PUBLISHER: Grand View Research | PRODUCT CODE: 1633736
PUBLISHER: Grand View Research | PRODUCT CODE: 1633736
The global automotive artificial intelligence market size is estimated to reach USD 14.92 billion by 2030, registering a CAGR of 23.4% from 2025 to 2030, according to a new report by Grand View Research, Inc. The artificial intelligence (AI) in the automotive industry is driven by factors such as government initiatives to incorporate autonomously and the growing demand for autonomous vehicles. Furthermore, the automotive industry's expansion will likely drive the artificial intelligence market. The automotive sector has benefitted from artificial intelligence and is one of the primary industries that use AI to augment and replicate human action. For instance, in March 2023, RoboSense announced the launch of the RS-Fusion-P6 (P6) automotive-grade solid-state LiDAR perception solution. The P6 LiDAR system is designed explicitly for level 4 autonomous driving and integrates cutting-edge software and hardware support, ensuring efficient and reliable perception capabilities for autonomous vehicles.
The advent of standards such as Advanced Driver Assistance Systems (ADAS), blind-spot alert, Adaptive Cruise Control (ACC), and increased demand for convenience features are attracting automotive providers to AI. AI mission-critical occurrences necessitate analysis, warnings, and directives. Automotive ADAS comprises various advanced sensors, such as LiDAR, Inertial Measurement Units (IMUs), radar, and cameras, as well as data connectivity and pressure and temperature sensors for constant uploads and downloads of surrounding conditions. The signal chain necessitates proper conditioning of sensor outputs and detection and reliable low-latency communications within the vehicle and the surrounding infrastructure.
AI has enormous potential in the automobile industry when embedded within the industry's products, production and manufacturing processes, and value-added chains. AI deployment is expected to contribute significantly to a safer, cleaner, more efficient, and more reliable mobility ecosystem. For instance, AI applications in connected and automated vehicles improve driver safety, monitoring, situational awareness, comfort, and trajectory prediction. It can lead to significant gains in performance and efficiency, such as enhanced logistical flows, traffic fluidity, and reduced fuel or power consumption.
In recent years, businesses manufacturing Automated Driving Systems (ADS) technology have substantially invested in live testing autonomous vehicles operating in virtual environments to assure their dependability and safety. However, the Covid-19 pandemic, which began in March 2020, prevented, disrupted, and delayed the achievement of these new product development test objectives due to its sudden beginning and continued resurgent impacts. A study published by Adrian Chen Yang Tan on March 10, 2022, used data from the California Automated Vehicle Test Program to ascertain how the pandemic impacted testing trends, resumptions, and test conditions. The study emphasized how crucial it is for government measures to encourage and facilitate the development of autonomous vehicles in pandemic situations.