The thought of having driverless cars was contemplated as early as the 1920s by Francis Houdina, who demonstrated a radio-controlled driverless car on the streets of New York City. So, the idea isn’t as new as it might seem to be. An early prototype of an automated car was even sponsored by General Motors at the 1939 World’s Fair.

Over the years, AI-powered cars have been depicted in the movies and have remained a strong part of our imaginations. While the idea has been quite exciting, the work done on this matter wasn’t substantial until now. This is because driving a car doesn’t involve simply following a set of rules or algorithm; rather it requires learning.

Even in 2018, the automotive companies employing AI only grew marginally by 3%. However, it has been predicted that by 2024, the value of AI in the automotive industry and cloud services will rise beyond $10.73 billion. An IHS report reveals that the install rate of AI systems in vehicles was 8% in 2015 but it is expected to grow to 109% by 2025.

AI Taking the Driving Seat

Before the automotive industry allows AI to take the wheel, they want to put it first in the co-pilot’s seat. It is a perfect choice to power the vehicles with advanced safety features and letting the manufacturers, customers, and regulators be comfortable with the idea of AI getting the license to drive.

Waymo is way ahead in developing a prototype and has even gone through basic testing, whereas Tesla TSLA has already launched vehicles which can self-drive on highways and controlled roads. Tesla’s Autopilot software can even check your calendar and take you to the destination without you telling it explicitly.

Detecting and Avoiding Equipment Failure

AI will help the automobile companies in manufacturing of the vehicles and management of the inventory. The quality control will also improve saving millions of dollars and preventing the companies from going bankrupt.

The costs can be unaffordable if a machine fails unexpectedly during the assembly line. AI-based algorithms can digest masses of data, detect anomalies, diagnose a problem and predict if a breakdown is imminent.

The potential impact of integrating AI in manufacturing would be 20% more availability of the equipment, a 10% decline in annual maintenance costs, and 25% lower costs spent on inspection of the machinery.

Intelligent Insurance Risk Assessment

Insurance companies are already looking for ways which will help in detecting or even reducing the risk involved in driving. AI has good news for the insurance customers too as it speeds up the process of filling a claim when an incident occurs.

AI can dig deep into the driver’s profile than just its driving history to evaluate the risk involved in his driving. From detailed medical assessment to a close eye on personal life, AI can find anything which can affect the driving ability of an individual.

The Bottom Line

The future is very promising for AI in the automotive industry. AI will help the companies in building better quality products and detecting the defects 90% better than human evaluation. The day isn’t far away when you’ll be looking for an autonomous driving car on Autotrader or Autolina and making the purchase of a vehicle equipped with IoT.