1 to 3 Years Computer Vision Back to Top
Analysis by: Kimberly Harris-Ferrante, James Ingham and Nick Ingelbrecht
Description: Computer vision (CV) is a process and set of technologies that involve capturing, processing and analyzing real-world images and videos to allow machines to extract meaningful, contextual information from the physical world.
Sample Providers: Amazon Web Services (AWS); Cape Analytics; Clarifai; Genpact; IBM; Microsoft Azure; Tractable
Range: Short (1 to 3 Years)
CV adoption is being driven by the price/performance of vision systems, heightened demand for monitoring and surveillance, and the need to automate image and video analysis to cope with increased volumes of unstructured image data. CV growth is less advanced in insurance compared with other verticals but taking off quickly as insurers seek new ways to improve claims, underwriting and customer service processes. The choice of where CV capabilities reside is primarily dictated by business considerations, availability of data/images to support the process, and the need for real- time intelligence, as well as potential data privacy and security concerns. CV adoption will be driven by increasingly sophisticated video and image search capabilities, fine-grained object and behavior recognition, improved metadata extraction, and advanced analytics. This data can be supplied by the consumer (e.g., submitting a picture of the damaged vehicle) or through a third-party data broker (e.g., video imagery of a city block). It can be combined with sophisticated rule engines and expert systems to deliver predictive and prescriptive analytics. Common challenges hindering CV providers include lack of suitable training data, ecosystem (channel, service and technology) dependencies, as well as lack of skills in adopter organizations. However, low-code/no-code platforms are rising to meet this challenge and are driving end-user adoption.
Mass: High
Gartner, Inc. | G00786204
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