Ways AI Will Revolutionize Automotive

The automotive artificial intelligence (AI) market is ready to soar, claims Next Move Strategy Consulting.

The consultancy’s recent report projects a market size of $25.78 billion and an impressive compound annual growth rate of 29.2% from 2024 to 2030.  Its study suggests government regulations and safety standards are the pivotal drivers for “propelling the growth of the automotive AI market.”

A strong emphasis exists worldwide on elevating vehicle safety, emissions reduction and environmental friendliness where automakers see AI as a potential solution. Oleksandr Odukha, vice president of mobility at Intellias, adds the automotive industry has made remarkable strides in integrating AI, machine learning, computer vision and natural language processing (NLP) into vehicles over the past five years. For example, advanced driver assistance systems, which are powered by AI, have become standard in new-vehicle models. They have a 92.7% adoption rate in the U.S. and are deemed to enhance safety, such as through obstacle recognition.

He claims they are reducing the estimated 3.59 million annual crashes, saving potentially 20,841 lives. Most ADAS features exist in Level 2-autonomy vehicles because Level 3 autonomous driving is “not implemented at large scale nor tested enough to introduce it into production,” he explains. NLP advancements concentrate on voice command recognition and driver verification.

Odukha adds: “AI can also decrease cost of vehicle manufacturing because it enables robots to assemble vehicles, lowering production costs and limiting manual work. The results we see today could lead to potentially cheaper manufacturing and enhanced road safety.”

Key Challenges

Several key challenges face the automotive industry with the rise of connected and autonomous vehicles (CAVs). David Mitchell, managing director of Futurice UK, says they include “steep development costs, limitations in current technology, regulatory barriers and concerns about data privacy.”

To address these challenges, he advises the industry to invest heavily in R&D with technology partners. Automakers also need to continue to lobby regulators because the industry needs favorable legislation. However, that legislation has to include privacy measures to address consumer concerns about how their data is used. Automakers must mitigate privacy concerns because many consumers won’t purchase CAVs without them.

Mitchell adds that standardization across the industry could also simplify the integration of various systems and technologies. As for the development costs, Odukha says an average ADAS bundle costs $1,950, which limits adoption. Standardization could reduce them. Yet there is still the need to build trust in the safety of autonomous cars. “Drivers understand that safety costs additional money, but still, it is difficult to guarantee predictable behavior of autonomous cars in so many scenarios on the road,” he explains. 

Industry Collaboration

Automakers need to collaborate to address these challenges, particularly regarding united core components development and continuous safety measurements. Odukha elaborates: “When it comes to safety, it's important for users to understand that a perfectly autonomous car doesn't exist yet. Therefore, the safety of these cars is measured by looking at incidents over millions of kilometers and comparing them to human-driven cars. The goal is to reduce these statistics over time.”

As for whether AI and machine learning (ML) are revolutionizing the automotive industry, Mitchell believes they are causing a seismic shift, particularly with CAVs. He claims they are enhancing not just safety but also the driving experience. AI and ML are also laying the groundwork for the top Level 5 autonomy.

Any revolution hinges on automakers overcoming the current hurdles. Full autonomy requires technological sophistication and there is a need to win public acceptance of the technology. Full autonomy can’t exist, too, without supportive regulations. He adds: “Generative AI may dominate the conversation for some time, with Large Language Model-based query assistants helping a driver at one end and generative code co-pilots supporting and reducing the cost of development at the other.”

Odukha finds a transition within the automotive industry that’s going in various directions. CAVs, electric vehicles, electrified vehicles and shared mobility continue to disrupt the industry. It’s not a complete revolution but an evolutionary process. It involves a rapid growth in EV adoption and it notes drivers who experience ADAS Level 2 and cruise control “prefer not to return to manual cars because these features provide added comfort,” he claims.