The automotive artificial intelligence market is skyrocketing upwards with no sign of stopping. This market is expected to grow at a CAGR (compound annual growth rate) of 39.8% from 2019 to $15.9 billion by 2027. Think about it: our homes are getting smarter, our devices are getting smarter, so why not cars?
4 Ways AI is Impacting the Automotive Industry (and Why it Matters)
There are many reasons to use AI in the automobile world, including the rising cost of operations, unhappy customers, declining sales, competition, and safety. We are living in a world where everything we use is “smart,” so it’s no surprise that our cars are becoming “smart” too. Below lists four major ways AI is impacting the auto industry:
1. Autonomous Automobiles
The idea of a self-driving car is exciting and scary at the same time. How do we know that we can trust these vehicles and completely drive with our hands off the steering wheel? So far, there have been two major instances of autonomous automobiles:
- Audi worked with engineers and psychologists for multiple years to “teach” a car how to drive safely, teaching the car that while the car gives the driver a “hands-free” option, the driver still needs to be alert and somewhat in control. This solution was integrated with their A8 model that uses facial recognition cameras to monitor the driver’s expression and detect if the steering wheel is being utilized. Audi taught the car that if the driver isn’t paying attention, it will alert them with audio or visual cues, and if that doesn’t work, the car will press on the brakes. If the driver still doesn’t acknowledge what is happening, Audi will turn on the hazard lights, pull to a stop, and unlock the doors.
- For completely driverless vehicles, nuTonomy (now Aptiv) used their technology, nuCore, to provide autonomous cars wherever they were needed to ensure safer roads, less traffic, and less pollution. In 2016, they launched their Robo-taxi pilot in Singapore, which was a success. nuTonomy also partnered with Lyft in Boston to test out their features in Boston’s Seaport District, which you can learn more about here.
2. Risk Identification and Emotion Detection
To improve driver safety and fleet management, BMW partnered with Allianz insurance group to develop a solution to track driver alertness and unsafe driving habits by leveraging Nauto’s cloud-based AI platform. Machines are learning emotions & moods by companies uploading pictures and processing them through machine learning algorithms. From there, the machine will calculate probabilities in terms of emotions such as anger, happiness, sadness, etc. This element is beneficial in detecting a distracted or reckless driver.
3. Machine Learning to Collect Valuable Data
Companies depend on machine learning algorithms to analyze and process data to ensure the use of AI is top-notch. Toyota just rolled out TRI (Toyota Research Institute) to use machine learning to understand Japan’s aging population. The number of those 60+ is expected to increase to 40% in the next 30 years. TRI wants to ensure that they can keep the aging population mobile and that the demographic group utilizes cars safely and effectively.
Machine learning can also help increase car sales. The learning module can collect data about a customer like their demographics, online activities, etc. For example, Cars.com used machine learning to help customize the car search process. It took the buyers’ personality quiz and matched cars unique to the buyer’s needs and personalities.
Machine learning also goes hand in hand with AI-powered advanced marketing. When you think about sales, you need qualified leads. Combining AI, data, and machine learning can help the automotive industry in obtaining sales. Think of social media: Instagram and Facebook rely on algorithms – so shouldn’t marketing rely on that, too? AI can analyze data and accurately target qualified prospects by suggesting products and services based on consumers’ searches and “likes” on social media. For example, if a user likes sweets or desserts, AI can suggest a nearby bakery shop. Like a user searches for cars online, AI can suggest certain car brands or dealerships based on the analyzed data. In short, machine learning can advance automated accessibility testing, support product owners in managing their accessibility status better, and eventually make the content more accessible.
4. AI For Auto Industry Websites
Many car dealership websites are turning to AI to help power their sales and marketing. AI technology is also helping them achieve web accessibility to navigate their site and browse available vehicles. Accessible, a leader makes the entire process to full Web Content Accessibility Guidelines (WCAG) and the Americans with Disabilities Act (ADA) compliance 100% automated, using machine learning and computer vision technologies. Over 113,00 websites rely on access to maintain their website’s accessibility state because failure to invest in web accessibility means that businesses are losing out on at least 20% of potential customers. An accessible website helps dealerships boost brand perception, show customers they care about those with disabilities and expand their market outreach.
Artificial Intelligence is only getting more advanced by the year. The impact to the automotive industry will be substantial and will increase value and efficiency in people’s lives – artificial intelligence will enhance quality, decrease risk, and improve the product and services offered by each auto brand. Using AI marketing and websites will help increase sales and drive up customer satisfaction by servicing everyone: those with disabilities and those without. The world will benefit from artificial intelligence, and it will be only a matter of time that flying cars will be an afterthought!