The automotive industry continues to be a hotbed of patent innovation. Activity is driven by cost reduction, enhanced customer experience, automation, efficiency, regulatory and industry standards, and the growing importance of technologies such as big data, cloud computing, machine learning, and advanced imaging technology. In the last three years alone, there have been over 1.7 million patents filed and granted in the automotive industry, according to GlobalData’s report on Artificial intelligence in automotive: AI in damage estimation. Buy the report here.
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However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilizing and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
300+ innovations will shape the automotive industry
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According to GlobalData’s Technology Foresights, which plots the S-curve for the automotive industry using innovation intensity models built on over one million patents, there are 300+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, autonomous on-demand logistics, end-to-end learning models, and adaptive driver alerting are disruptive technologies that are in the early stages of application and should be tracked closely. Vehicular vision, adaptive cruise control, and predictive acceleration control are some of the accelerating innovation areas, where adoption has been steadily increasing.
Innovation S-curve for artificial intelligence in the automotive industry
AI in damage estimation is a key innovation area in artificial intelligence
AI in damage estimation refers to the use of artificial intelligence techniques, such as image processing and machine learning algorithms, to automatically estimate the repair cost and identify the extent of damage to a vehicle or property. This involves analyzing images of the damaged vehicle or property, detecting external damage, inferring internal damage, and calculating an estimated repair cost based on a parts database and labor costs.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 30 companies, spanning technology vendors, established automotive companies, and up-and-coming start-ups engaged in the development and application of AI in damage estimation.
Key players in AI in damage estimation – a disruptive innovation in the automotive industry
‘Application diversity’ measures the number of applications identified for each patent. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of countries each patent is registered in. It reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to AI in damage estimation
| Company | Total patents (2010 - 2022) | Premium intelligence on the world's largest companies |
| American International Group (AIG) | 24 | Unlock Company Profile |
| Mitchell International | 26 | Unlock Company Profile |
| State Farm Mutual Automobile Insurance | 479 | Unlock Company Profile |
| Verisk Analytics | 20 | Unlock Company Profile |
| LyondellBasell Industries | 13 | Unlock Company Profile |
| USAA | 19 | Unlock Company Profile |
| Clearlake Capital Group | 93 | Unlock Company Profile |
| Cox Enterprises | 135 | Unlock Company Profile |
| Baidu | 41 | Unlock Company Profile |
| Flex | 56 | Unlock Company Profile |
| Alphabet | 96 | Unlock Company Profile |
| Pictometry International | 12 | Unlock Company Profile |
| CoreLogic | 17 | Unlock Company Profile |
| Alibaba Group | 246 | Unlock Company Profile |
| Lear | 26 | Unlock Company Profile |
| Allstate | 95 | Unlock Company Profile |
| Ping An Insurance (Group) | 211 | Unlock Company Profile |
| The Toronto-Dominion Bank | 23 | Unlock Company Profile |
| Leonard Green & Partners | 27 | Unlock Company Profile |
| Advanced New Technologies | 89 | Unlock Company Profile |
| International Business Machines | 32 | Unlock Company Profile |
| Donan Engineering | 13 | Unlock Company Profile |
| Zendrive | 21 | Unlock Company Profile |
| Healthy io | 26 | Unlock Company Profile |
| Vista Equity Partners | 16 | Unlock Company Profile |
| NetraDyne | 16 | Unlock Company Profile |
| Tractable | 86 | Unlock Company Profile |
| Taikang Insurance Group | 35 | Unlock Company Profile |
| Theator | 18 | Unlock Company Profile |
| Yembo | 30 | Unlock Company Profile |
Source: GlobalData Patent Analytics
State Farm Mutual Automobile Insurance is one of the key patent filers in AI in damage estimation. The company’s Computer Vision and Image Analysis helps in AI-driven computer vision systems. It can analyze images and videos of damaged vehicles to assess the extent and type of damage. Convolutional neural networks (CNNs) are often used to identify and categorize dents, scratches, and other damages. Alibaba Group, Ping An Insurance (Group), and Cox Enterprises are some of the other key patent filers in this area.
In terms of application diversity, Flex leads the pack. Cox Enterprises and Theator stood in the second and third positions respectively. By means of geographic reach, Alphabet held the top position followed by Flex and Clearlake Capital.
To further understand the key themes and technologies disrupting the automotive industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Automotive.
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
