The auto industry has long been a leader in the use of AI. It's not surprising, then, that this trend is accelerating as more companies look to take advantage of the technology and its potential benefits.
The potential market value of AI-driven cars and trucks could reach $7 trillion by 2050, according to McKinsey & Company. The four major trends driving interest in AI are:
Increased demand for autonomous vehicles (AVs)
Growing adoption of electric vehicles (EVs)
Shifting consumer preferences toward shared mobility services like car sharing or ride hailing
Advances in connectivity that allow vehicles to communicate with each other, infrastructure and other systems.
The automotive industry is one of the most promising markets for AI technology. It offers many opportunities for businesses to develop new products and services, but also presents challenges in terms of privacy and safety.
AI can help cars achieve their full potential by integrating with other technologies in the vehicle, such as sensors and cameras. This will make it easier for drivers to access information while driving without having to look down at their phones or other devices. For example, if there's an accident ahead of you on the road, your car could notify you via voice command that there is congestion ahead so that you can take an alternative route without having any distractions from looking at maps on your phone while driving.
The regulatory framework for autonomous vehicles is still being developed by state and federal governments. Some of these important questions include:
What type of vehicle classification should AVs be given? Are they cars or trucks? This will determine whether they are subject to normal traffic laws or highway safety laws.
How do you regulate the testing phase, which may involve thousands of vehicles operating in a limited area at any given time?
Do you allow autonomous vehicles on public roads without a human driver present (known as "driverless" cars)? If so, what kind of restrictions would apply during this stage?
AI in Manufacturing
AI can be used to optimize the supply chain. For example, it can reroute shipments and change production schedules based on customer demand. This is especially useful for businesses like auto manufactures who operate globally because it allows them to respond quickly when there's an issue with one of their products or services.
A good example of this is Amazon's Prime Air drone delivery service: if you order something online, it will be delivered by drone within 30 minutes! As OEMs move to take more control of the buying process, they will need AI to scale ordering and delivery.
Autonomous vehicles will also reduce the number of accidents, which can be a big cost for automakers. In 2017 alone, there were more than 40,000 traffic fatalities in the United States. The National Highway Traffic Safety Administration estimates that 90% of these accidents were caused by human error and could have been prevented if autonomous vehicles had been available on the road at that time.
Automakers are also interested in using AI to make cars more efficient by reducing congestion and wasted fuel consumption due to stop-and-go driving patterns or inefficient traffic flow patterns caused by human drivers' poor judgement about when it's safe to merge onto freeways or exit off ramps without coming too close to other vehicles (which increases both congestion and pollution).
The Future of AI in the Automotive Industry
The future of AI in the automotive industry will be characterized by never before seen collaboration between companies and governments, sharing data about performance, driving infrastructure modernization and creating a safer, cleaner, more reliable transportation industry. The question for the modern automotive company leader is what role will your company play in the creation of this future? Reach out to the Auto Market Insights team to gain insights on how you can ensure you're capturing more than your fair share of the AI market.