ChannelLife New Zealand - Industry insider news for technology resellers
Story image
Artificial intelligence prominent in automotive market
Fri, 26th May 2023

From software to hardware and chipsets, the role artificial intelligence in the automotive market is prominent, according to new analysis from Future Market Insights.

Artificial intelligence in the automotive market is set to record a robust CAGR of 55% during the forecast period. The market holds a share of US$ 9.3 billion in 2023 while it is anticipated to cross a value of US$ 744.39 billion by 2033.

The research report on artificial intelligence in the automotive market explains that the advent of autonomous vehicles with ADAS and auto-driving modes are adopting artificial intelligence solutions that integrate with automotive technology, leading to services like guided park assist, lane locater, etc.

The restoration of the automotive industry post-pandemic with extensive research and development programs is flourishing the sales of Artificial Intelligence in automotive. Personalised vehicles with AI features are on high sales, as they deliver ease in the end user’s life. The better customer experience with AI-enabled applications for autonomous operations is expanding the demand for Artificial Intelligence integrated automotive systems. Also, automotive companies integrate with strategic companies that specifically cater to AI integration. Automotive engineers designing new cars with driving assistance are likely to fuel the market growth.

Artificial intelligence in the automotive market outlook states that the future of automotive companies using AI for their transformed transmissions is also fuelling the sales of AI-integrated automotive systems. The design and production of new vehicles using AI and automation are essentially what is driving the sales of fully digitalised electric vehicles. New vehicles have AI-integrated systems that observe the driver’s driving pattern and keep it in their systems for advanced guidance and assistance. It also provides data about the temperature settings, music, and ambiance. The integration of AI with machine learning, and Natural Language Processing (NLP), is another factor that supports AI in automotive market expansion.

Future vehicles are expected to implement high-end AI technology, as they are supposed to work on autopilot systems. Hence, AI integration becomes important for future automotive manufacturing. Government and authorities adopting sustainable technology while pushing the same agenda over the technology and automotive vendors are fueling the demand for artificial intelligence and machine learning technology. AI technology is not just part of the final automotive product but becomes an important part of its construction of it. AI-backed robots are helping the manufacturing of vehicles with higher precision. AI along with machine earning also navigates through traffic in an autonomous driving operation.

For instance, Motional, a joint venture between Aptiv and Hyundai Motor Group, delivers advanced autonomous driving technology. It has implemented three sensor types, LiDAR, Radar, and cameras. These AI input sources feed enough information to the AI system to analyse and command. Unlike Motional, which outfits vehicles with autonomous capabilities, some companies are also creating self-driving vehicles from scratch. Application of AI in driver assistance and autonomous delivery of items are the latest fronts added to its applications and are likely to fuel the market growth. These factors are anticipated to transform Artificial Intelligence (AI) in the automotive market.

Future Outlook for Artificial Intelligence in Automotive Market 
Short-term Growth: The market was affected by the COVID-19 pandemic and research & development. However, the machine learning processes fuelled the demand for Artificial Intelligence in automotive systems. The market has built its base during this phase of its growth with new integration-based programs. Companies with personalised automotive systems also fuelled the demand for Artificial Intelligence in automotive.

Mid-term Growth: The new and advanced project regarding research of AI’s application in different automotive machines. Industries 4.0 with its components brushing up the applications of AI in automobiles. For instance, machine learning plays a crucial role in understanding the driving pattern, while AI analyses it and gives assistance to the driver.

Long-term Growth: Strong marketing campaigns, along with the normalisation of EVs and hybrid vehicles, are likely to give the market a large push. People with increased per capita income are investing in the upcoming technology. This is likely to have a positive impact on the market. Artificial intelligence in the automotive market is anticipated to record a CAGR of 55% between 2023 and 2033.

What Factors Drive and Restrict Artificial Intelligence in the Automotive Market?
From software to hardware and chipsets, the role of AI in modern vehicles is prominent. AI has proved itself to be the transforming technology of the future, and its integration with any smart device becomes a necessity. Vehicles with smart AC controls, lighting, park guide assist systems, and autonomous steering systems demand software and programming support. The AI-integrated transmission comes into play here with its enhanced machine-learning system and active memory. AI remembers actions and utilises memory for helpful decision-making during the drive. It comes with features like automatic lane-shift, overtaking, and more. Hence, the growing requirement for autonomous cars is fuelling market growth. The rapidly changing trends of the Advance Driver Assist System (ADAS) are another driving factor for the market. Increasing awareness around these vehicles and the importance of CaaP business models are anticipated to fuel the sales of Artificial Intelligence (AI) in automotive.

Key restrictions for the market can be explained as the limited application of sensors and equipment that strengthens AI and ML systems. Another roadblock to the market’s success is software and hardware malfunctioning, which makes the end user skeptical about its application in the first place.

The United States Artificial Intelligence in the automotive market is recording a significant CAGR between 2023 and 2033.

The United States is expected to dominate the North American artificial intelligence in the automotive market, attributed to the sale trends of autonomous vehicles and electric vehicles with fully automatic programs. The new businesses designing vehicles based on self-driving prospects are another factor that thrives the regional growth. The programs for substantial human growth and environment preservation are also supporting this trend of adopting EVs. The presence of EV giant Tesla in the United States also fuels the demand for AI in automotive solutions.

The increased per-capita income, highly advanced automotive engineering, and collaboration between vehicle companies and AI technological vendors are creating new opportunities for the market while increasing the overall demand for Artificial Intelligence in automotive solutions.

Higher Research and Development Investments, along with Advanced AI Software Support are Propelling the Growth in China
China plays an important role in the thriving market space. The rapid adoption of AI and ML technologies in electric vehicles is likely to fuel the demand for AI software and hardware tools. Chinese automotive giants have extended their research and development programs to analyse the autonomous driving concept so that it can be launched on a bigger scale in the future. The application of AI during vehicle manufacturing as OEM implants is another factor driving the use and sales of AI in automotive.

Adoption of EVs and Autonomous Vehicles with the Biggest Manufacturing Hub is Transforming the Market in Europe
In the countries like Germany, France, Spain, and Poland, the leading automotive manufacturing spaces are trying their best to integrate AI systems in their vehicle transmission. From fossil fuel-based vehicles to EVs, the plan is to digitise the wheels while putting the driver at ease. Thus, the demand for artificial intelligence in automobiles is at the boom, supporting the global market. Germany itself is a vehicle manufacturing hub and is extending its research facilities to implement AI and ML-based technologies in its full manner.

The software segment leads in the component category, with a leading anticipated value of US$ 200 billion in 2033. The increased application of autonomous vehicle services like paring support, self-driving, AC controls, and advanced music systems are all controlled by the software. The OEM software and the third-party software are the available options. While companies don’t experiment with their pre-installed, outside vendor support and personalise the AI platform according to the need.

The Advent of Self-driving Cars, along with ADAS and Steering Assistance Systems, is propelling the Segment growth
By application, the fully autonomous segment thrives at an anticipated value of US$ 30 billion by 2033. The growth is attributed to the trending vehicles with driving assistance or autonomous control. The parameters for self-sustaining driving, to put it simply, are determined by how much control the AI is given. Advanced AI systems are being produced by technology companies and automakers, particularly for driverless vehicles.

The global artificial intelligence in the automotive market is highly fragmented, where players are advancing their systems through the integration of sensors and other components. The AI vendors are anticipated to introduce software support to vehicles that make them fully autonomous.

Market Developments

BMW AG is expected to digitise the manufacturing space with innovative solutions, integrating the digital mobility program. The upcoming BMW projects are anticipated to involve AI-based transmission and programming. Tesla Inc has revised its artificial intelligence and autopilot technology, which are counterparts of each other. The company is expected to achieve its autonomous claims with the concepts like neural networks, autonomy algorithms, code foundation, evaluation infrastructure, dojo system, and chip.