AI applications in the automotive industry are huge, from self- driving cars to voice commands systems to build a car with more convenience and safety, Automated Guided Vehicles (AVGs) are being used to move materials in the plant units without human intervention.  AI has a huge potential to innovate the automotive industry to gain a strong foothold. Conversational assistants integrated into cars have NLP and ML algorithms enabled to provide the driver with ease of delivering commands to the system. AI also has other advantages like to imitate, develop, and assist human actions while leveraging its algorithms in precision with machine-based frameworks.

According to Allied Market Research, the global automotive artificial intelligence market is expected to reach $8,887.6 million by 2025, from $445.8 million in 2017, growing at a CAGR of 45.0% from 2018 to 2025. The growth of AI in the automotive market will increase if there’s a demand for autonomous automobiles and customer driving experience enhancements. Customer’s most preferred AI interface is voice control because it allows the drivers with hand-free control which reduces the probability of getting distracted from the road. Today voice assistants are ruling the tech industry with its advanced features like talkback, interactive experience, real-time insights, etc. The concept of self-driving cars has been there in the automotive industry for quite some time and to materialize this concept artificial intelligence plays a very crucial role. AI has its applications in many other industries too but the scope of innovation is more in the automotive industry. This cutting edge technology leads to many automobile manufacturers designing and developing the best AI-enabled automotive technology. Artificial intelligence’s subset ML enhances the AI automotive features by learning the driver’s movements and expressions from the videos/images captured from the cameras integrated into the car that helps the system to learn and perform accordingly. AI in the automotive industry is estimated to exceed $10,73 billion in the next five years (source: medium.com). The future of automotive vehicles relies on AI and its algorithms.

To get a deeper understanding of what AI/ML brings to the automotive industry, in this article we will discuss about its prominent applications in this industry.

1. Cloud computing: AI-powered vehicles require big data to efficiently perform their task and for training purposes. This application makes sure the data is available 24/7 to the system to execute AI technologies like predictive analytics, big data access, and centralized connectivity. The cloud service further helps in predicting the maintenance required by monitoring the sensors for identifying irregularities in operation. It helps the drivers to get their required items easily available by recommending them the nearest buying point and also let them pay for the fuel from inside the car in gas stations. Cloud computing allows automotive marketers to brand their product for a precise target market rather than targeting the audience as a whole.
2. Deep learning: Deep learning enhances AI activities in automobile functioning thereby avoiding the chances of having any problems. It automates the tasks which make the work of the driver easier to manage the vehicle function. It has brought a wave of innovations in the automotive industry by its applications in advanced driving assistance systems and self-driving. Deep learning has lately instigated a huge headway in this sector.
3. Infotainment systems: Features like eye tracking, speech and gesture recognition, monitored driving, etc. comprises the infotainment. These are some of the advanced features drivers’ expect from automotive vehicles. With artificial intelligence developing the infotainment systems have become better and bigger. It receives data from the cloud service neural networks for operational purposes.
4. Cognitive capabilities: Cognitive frameworks are expected to work like a human which would interpret a genuine circumstance, so as to do that, profound knowledge of unstructured data is required. Auto manufacturers have now begun consolidating this into their vehicles. With capabilities like identifying patterns, natural language interpretation, cognitive analytics gives us a path to mine and comprehend this data.

AI innovation is constantly developing and the reception of this utilizing innovation is welcoming; thanks to the engineers and analysts who have been able to structure the application to the optimized computational capacity to attain the degree of flawlessness.