5 Useful Applications for Artificial Intelligence in Automotive

5 Useful Applications for Artificial Intelligence in Automotive

As car manufacturers from around the world are constantly innovating to introduce state of the art features, insurance companies have leveraged data and technology to serve users with a personalized insurance cover tailored to individual’s driving profile. Let us first address the elephant in the room – innovation through AI. Artificial intelligence in the automotive industry has led to immeasurable efficiency gains that support insurers to speed up data classification process during risk assessment and provide vehicle damage evaluations while enhancing quality control. Therefore, AI systems combined with robotic solutions rely on advanced technologies that are widely applied and essentially offers insurers to provide a pleasant and productive experience.

A recent study by Gartner predicts that the total number of new vehicles equipped with AI interception rose from 137,129 units in 2018 and is expected to increase to 745,705 units by 2023. Thus, the size of the global automotive market of autonomous vehicles is predicted to reach as high as $37 billion.

The role of Artificial Intelligence in today’s automotive industry

The potential of artificial intelligence in the automotive substantially benefits insurance providers not only by eliminating tedious manual paperwork but also helps in attracting more customers with its digitally optimized functionalities. Therefore, AI-powered tools ensure insurance companies to provide open-end queries and resources for fulfilling customer demands and making the self-driving experience smooth and hassle-free.

Today’s car insurers use AI to increase production, manufacturing, and supply chain efficiency to make driving safer and more convenient for users. Furthermore, Artificial intelligence in automotive – using cloud computing, deep learning, and the cognitive system will help measure vehicle performance 24*7 and install alerts for replacing insurance adjusters in case of any collision or vehicle damage. For example, if a vehicle meets with an accident, then enable insurance providers to assess damages by generating historic invoices and spare-parts catalogues with the use of real-time data and image sensing data.

5 Useful applications in Artificial intelligence automotive:

Automation has been a major part of the automotive industry for decades now, but with AI – insurance processes are performed with fewer errors and improved customer satisfaction. Let us see how modern applications can leverage the capabilities of artificial intelligence in the automotive industry. We have gathered 5 useful AI automotive applications that can efficiently support car insurers to capture their full potential.

1. Driver Behavior analytics:

Driver distraction is one of the leading reasons for road accidents. Artificial intelligence-based automotive applications offer valuable in-car sensors like real-time image analytics, voice-enabled notifications, speech recognition and object detection. Such listed features rely heavily on assisting the driver regarding traffic updates, and weather changes or notifying about any possible dangers like driving conditions, lane departure and forward collisions.

Most intuitive feature of in-car sensors

Besides autonomous driving features, Artificial intelligence is extending its significance in analyzing vehicle performance and exploring recent driving insights by accessing in-car functionality and sensor data stored in the cloud. For instance, Tesla aimed to constantly update its AI software developed for driver assistance and measure self-driving to ensure driver and co-passenger safety.

2. Quality Control: 

Artificial intelligence in the automotive industry can enable insurance companies to take timely actions with the use of various applications that are based on data gathering, sensor data and other image interfaces. In addition, this can inform users about certain components of performance, evaluate vehicle quality, and set system alerts of any maintenance if required or any spare parts that need to be replaced depending on data received by sensors. Furthermore, car manufacturers also use AI-powered quality control systems to detect technical flaws before getting installed.

For Instance, Deloitte has launched trained deep learning and AI detection solutions to accurately assess mandatory vehicle inspection and predictive maintenance for quality analysis based on data collection and processing that save inspection time and effort. 

3. Rapid Document Digitalization with OCR: 

As legacy insurers still largely rely on traditional paper-based forms and standard print documents. Optical character recognition (OCR) a tech-enabled process, can be a big game-changer in the automotive world. Instead of manually re-typing information, insurance agents can fully make the best use of document creation via digitalization to accurately capture and reconcile data from paper-based documents and augment it into digital formats using artificial intelligence and computer vision techniques. Therefore, OCR applications can help insurers onboard customers easily through website portal and other omnichannel ways that enhances operational efficiency and ease the KYC process.

A recent Gartner study results that such an increased state of automation in digital document creation can drive up to 80% savings in cost and resources for each process.

4. Data-driven personalized services 

Ensuring driver and passengers safety and satisfaction is crucial, so car manufacturers invest in improving their vehicle performance with all kinds of AI-powered automotive applications that helps to upgrade the passenger experience. Some of the advanced capabilities using voice and video assistance that include offering personalized services like health state monitoring, customized music playlist, traffic, news updates, claim processing status, car-parking alerts etc.

For instance, BMW enabled the use of AI-powered models by introducing the voice assistant that enables passengers to search or listen to their preferred music and get quick updates and alerts using automation with less effort while on the road.

5. Risk identification and estimation 

Artificial intelligence in automotive can benefit repair cost estimation when combined with computer vision and using deep learning insights that help detect risks and extent to calculate repair costs. A Deloitte survey stated that AI-enabled damage and repair assessment increases inference time by two seconds and the model achieves 97% accuracy. Furthermore, this will ease the claims process by assessing automated damage value estimation based on video recognition, image analytics and sensor data in combination with invoice data. Therefore, the classification model uses an advanced edge deployment mechanism while identifying car damage estimates that can eliminate human effort.

Using AI to evaluate car damage

The future of artificial intelligence in the automotive world: 

As mentioned in our overview, artificial intelligence in the automotive industry offers a variety of applications so that car manufacturers can easily deploy for designing, production, and supply chain and enabling predictive maintenance for any kind of vehicle damage inspection. Therefore, AI also harnesses the power to monitor driver behavior and offer personalized services to passengers and deliver experiences like smart wireless transportation, in-car sensor data for risk detection and instant insurance claim filing.

Artificial intelligence in automotive can also segment claims cases concerning vehicle damage or risk assessment by using factual and predicted claims characteristics which helps them automate labor-intensive tasks relating to different operational inspections. To explore more check out our blog that highlights how image analytics is aiding claims intelligence in auto-insurance that explains the need for AI and addresses the key solutions which help futureproof auto claims seamlessly.

Interested to learn more about the uses of artificial intelligence in the automotive industry and how these benefits from its implementations? Every subject will require an individual approach. Reach out to our expert team and get the best solutions.

Aishwarya Chandrasekhar

A content marketing enthusiast, currently on a quest to channel my vision, creative thinking and innovative strategies through my writing. I believe that each day presents itself as an opportunity to learn, grow, and set path for driven goals

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